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Marco Diaz

Mobile and payments engineering leader | DevEx and enterprise AI platform operator

Marco Diaz portrait
  • Technical engineering leader with 10+ years in software and 5+ years in people leadership, grounded in mobile commerce, payments, and platform reliability.
  • Led Walmart mobile and fintech-adjacent payment initiatives across Android, iOS, backend, product, risk, and legal constraints.
  • Built and launched Sentra Residence on sentraia.dev: a production residential operations product across web, mobile, Supabase, QR access, offline queues, audit history, and real resident/guard workflows.
  • Now operate enterprise AI tooling across OpenAI, Microsoft/GitHub Copilot, and Atlassian Rovo as an admin, vendor partner, alpha-style evaluator, and enablement lead.
  • Turn Codex admin work into enterprise AI enablement: workshops, golden prompts, reusable runbooks, scorecards, and workflow standards with guardrails.
Walmart Payments Scale: Mobile + backendWalmart Leadership Scale: 10 FTE + 15 contractorsSDLC Automation: Jira -> Codex -> GitHub
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30-second-signal.md

30-Second Signal

The fastest way to understand the range before choosing a deeper hiring lens.

Engineering depth

10+ years

Hands-on software delivery across Android, React Native, frontend, backend integration, CI/CD, and production platforms.

Leadership scope

5+ years

Engineering management across Walmart mobile payments, senior IC growth, FTEs, contractors, and critical delivery programs.

Scale signal

Walmart payments

Customer-facing mobile, wallet, tender, checkout, One Pay, Pay Over Time, EBT, Walmart Cash, Gift Cards, and EV Charging work.

Current edge

Enterprise AI

Codex admin/operator work across OpenAI, Microsoft/GitHub, Atlassian Rovo, enablement systems, and SDLC automation patterns.

profile.lens

Choose a Hiring Lens

Pick a lens and the page immediately reshapes around that hiring conversation.

?focus=all

Role-Fit Lanes

Start with the conversation closest to the role you are hiring for.

Full Profile

Mobile builder, Walmart payments leader, and enterprise AI enablement operator.

Recruiters and hiring managers who want the full leadership + technical range before deciding where to go deeper.

Engineering range

10+ years

Leadership scope

5+ years

Current edge

AI + DevEx

all.profile

Full Profile

Mobile builder, Walmart payments leader, and enterprise AI enablement operator.

Use this view for the complete story: strong IC foundation, 5+ years of engineering management, customer-critical payments, production personal products, and current AI/DevEx leadership.

Best fit

Recruiters and hiring managers who want the full leadership + technical range before deciding where to go deeper.

LeadershipMobilePaymentsDevExAI ToolingPlatform

Engineering range

10+ years

Hands-on software background across Android, Expo/React Native, frontend, backend integration, CI/CD, Supabase, and platform workflows.

Leadership scope

5+ years

Engineering management experience across Walmart payments and current DevEx platform influence.

Current edge

AI + DevEx

Admin/operator work across Codex, GitHub Copilot, and Atlassian Rovo with enterprise rollout, alpha-style evaluation, scorecards, and workshop enablement.

Capabilities

Where I create leverage

  • Mobile and payments delivery
  • Engineering management
  • Developer productivity
  • Enterprise AI adoption
  • Personal production product ownership

Operating style

  • Clear ownership
  • Reusable systems
  • Measured adoption
  • Guardrails over heroics

Modern stack

Core systems

AndroidExpo/React NativeTypeScriptNext.jsSupabaseCI/CDAI tooling

Hiring signals

  • Strong fit for roles that need a leader who can speak deeply with engineers and still manage cross-functional execution.
  • Credible as both a platform leader and a builder because the recent work includes shipped products, workshops, admin controls, and measurement systems.
  • Best conversations: Senior Engineering Manager, Staff Engineer DevEx, AI Enablement Lead, Mobile Platform Leader.

sdlc.operating-model

AI-Assisted SDLC Operating Model

AI-assisted SDLC loop

The developer-day flow I am building toward: fewer handoffs, clearer ownership, and governed automation from Jira to deployment updates.

  1. 01

    Jira intelligence

    Daily ticket briefings, priority context, issue creation, search, updates, notifications, and escalations.

  2. 02

    Codex planning

    Plan Mode, repo context, constraints, tests, worktrees, and agent-managed subtasks.

  3. 03

    GitHub PR flow

    Implementation branches, PR creation, peer review handoff, AI review support, and CI feedback.

  4. 04

    Human gates

    Engineer and peer approval for code review, merge, release, and incident-sensitive changes.

  5. 05

    Work-item updates

    Jira summaries, status changes, deployment notes, and stakeholder notifications after the work moves.

How a developer moves from ticket context to shipped work with humans still owning the important decisions.

sunnyvale-walmart-scale.arc

Sunnyvale Walmart Scale Arc

The Sunnyvale Walmart chapter: from Android delivery to mobile payments leadership and fintech-adjacent scale.

  1. 012017-2018

    Walmart Labs Android

    Sunnyvale entry into Walmart-scale mobile

    Delivered Android capabilities for Walmart Grocery, payment-adjacent journeys, production fixes, performance improvements, and mobile regression confidence.

    MobilePaymentsReliability
  2. 022018-2021

    Senior Mobile Engineer

    Grocery, checkout, and payments-adjacent scale

    Designed and delivered pickup, check-in, checkout, delivery, favorites, search, and payments flows across Java, Kotlin, React Native, backend integration, analytics, CI/CD, and production observability.

    MobilePaymentsReliability
  3. 032021-2026

    Mobile Payments Leadership

    Engineering Manager to Senior Manager

    Grew from senior IC into management, led mobile payments roadmaps, coordinated iOS/Android/backend/product/legal/risk partners, and scaled operating cadence across FTEs and contractors.

    LeadershipPaymentsBackend
  4. 042022-2026

    Senior Manager II Payments

    Fintech-adjacent Walmart delivery

    Led One Way to Pay, One Pay migration workstreams, Pay Over Time, EBT, Walmart Cash, Gift Cards, EV Charging, release confidence, and peak scope across 10 FTE plus 15 contractors.

    LeadershipPaymentsReliability

Operating Thesis

I build systems that make high-performing engineers faster without making the organization less safe.

The throughline from Android to Walmart payments to enterprise AI is operating leverage: reusable workflows, clear ownership, strong release habits, and automation that keeps humans in control at the important gates.

01

Speed is only useful when quality, auditability, and ownership improve with it.

02

AI adoption should reduce handoff friction across the SDLC, not create a second shadow process.

03

The best platform work is visible in onboarding time, PR flow, release confidence, and developer trust.

leadership-signal.md

Executive Signal

Builder. Manager. AI platform operator.

The signal is rare range: 10+ years shipping software, 5+ years leading Walmart mobile/payments teams, and current enterprise AI admin/operator work with OpenAI, Microsoft/GitHub, and Atlassian tooling. I can lead teams, understand implementation risk, and turn AI into measurable SDLC acceleration.

Engineering depth

10+ years

People leadership

5+ years

Walmart scale

Mobile payments

AI platform leverage

OpenAI + Microsoft

01

AI enablement with governance

I can help an organization adopt AI tools without losing control of cost, access, security, or engineering quality.

  • Operate across Codex, ChatGPT Enterprise, GitHub Copilot, Microsoft tooling, Atlassian Rovo, and GitHub-integrated workflows as an admin/operator and enablement partner.
  • Turn Codex admin responsibility into a scalable enablement system: 101, 201, 301, and leaders sessions covering first wins, configurations, MCPs, skills, automations, SDK/headless usage, guardrails, and rollout metrics.
  • Validated ChatGPT + Rovo Jira workflows with user-permission boundaries, explicit approval prompts, and extensible patterns for create, search, update, summarize, notify, and escalate.
AI ToolingDevExPlatformLeadershipReliability
02

DevEx systems, not one-off fixes

I turn local wins into templates, scorecards, runbooks, and adoption paths that other teams can actually reuse.

  • Packaged Codex 101 into an Epic plus seven workstreams covering strategy, prompt validation, materials, facilitation, delivery, and retro.
  • Created sprint-demo material that framed workshop enablement, SDLC automation, and connector assessment as repeatable operating models.
  • Designed AI productivity scorecards around adoption, manual hours saved, confidence level, and operational risk.
DevExPlatformAI ToolingLeadership
03

Software delivery lifecycle automation

I automate the developer day from ticket context to PR, review, merge, deployment handoff, and ticket updates.

  • Use ChatGPT + Rovo to help developers start the day with Jira summaries, priority context, issue creation, search, update, notification, and escalation workflows.
  • Use Codex and GitHub-integrated workflows to move from ticket intent into implementation, agent-managed subtasks, PR creation, peer review, AI code review, merge, and deployment support.
  • Keep the workflow enterprise-ready with approval prompts, least privilege, auditability, explicit handoffs, and modular automation templates teams can tailor.
AI ToolingDevExPlatformReliabilityLeadership
04

Mobile, payments, and people leadership

The AI/DevEx work is additive, not a replacement for deep delivery experience in mobile, fintech, and team leadership.

  • Led Walmart mobile and payments work across One Way to Pay, One Pay, Pay Over Time, EBT, Walmart Cash, Gift Cards, and EV Charging.
  • Grew from Android/mobile IC roots into 5+ years of engineering management with peak scope of 10 FTE plus 15 contractors.
  • Continue building production software through Privada Reforma across web, Expo/React Native, Supabase, QR access, offline sync, and audit logs.
MobilePaymentsLeadershipReliability

Best next conversations

  • Senior Engineering Manager for mobile, payments, platform, or internal tools teams.
  • Staff Engineer or DevEx lead responsible for CI/CD, onboarding, golden paths, and AI-assisted delivery.
  • AI enablement leader for organizations that need governed rollout, practical workshops, cost awareness, and real adoption metrics.

proof-timeline.md

Proof Timeline

A fast read of how the story compounds from builder to payments leader to enterprise AI operator.

  1. 012013-2018

    Android and mobile builder

    Built native Android and mobile commerce foundations before moving into larger Walmart delivery systems.

    Hands-on implementation depth, device reality, CI/CD, QA automation, and production debugging.

    MobileReliabilityFrontend
  2. 022018-2026

    Walmart payments leader

    Led customer-critical payment journeys including One Way to Pay, One Pay, Pay Over Time, EBT, Walmart Cash, Gift Cards, and EV Charging.

    Fintech-adjacent mobile scale, legal/risk alignment, backend coordination, incident readiness, and release discipline.

    PaymentsLeadershipMobileReliability
  3. 032020-2026

    Senior engineering manager

    Scaled from senior IC into 5+ years of management with peak scope of 10 FTE plus 15 contractors.

    Operating cadence, coaching, team design, contractor-to-FTE ownership, and measurable productivity improvement.

    LeadershipPlatformReliability
  4. 042026-now

    DevEx and enterprise AI operator

    Operate Codex, ChatGPT Enterprise, GitHub Copilot, Microsoft tooling, and Atlassian Rovo across workshops, scorecards, and SDLC automation.

    Safe AI adoption, Jira-to-PR automation, reusable enablement systems, measurement, and executive-ready rollout thinking.

    AI ToolingDevExPlatformLeadership

quick-proof.sh

Quick Proof

$ opex_ai_scorecard:

Designed + coded cross-org scorecard

Built an OPEX productivity scorecard to track AI adoption and measurable improvements across Walmart and Thermo Fisher.

$ enterprise_ai_admin:

OpenAI + Microsoft tooling admin

Partnering directly with OpenAI and Microsoft while operating enterprise AI tooling, rollout guardrails, and enablement paths.

$ codex_201_advanced_workflows:

Advanced Codex training built for teams

Created Codex 201 material covering configurations, MCPs, skills, automations, multi-agent workflows, worktrees, and long-horizon tasks.

$ codex_301_agent_automation:

Advanced Codex automation track

Prepared Codex 301 material covering permissions, sub-agents, Plan Mode, memory, Windows sandboxing, ExecRules, SDK/headless mode, CI bots, and harness engineering.

$ codex_for_leaders:

AI-native engineering leadership session

Built manager-focused enablement around operating model, governance, adoption metrics, quality, security, and scaling Codex through champions.

$ rovo_connector_validation:

ChatGPT + Rovo Jira workflows

Validated natural-language Jira create, search, update, summarize, notification, and escalation patterns through approval-gated Rovo actions under existing user permissions.

$ sdlc_automation_flow:

Jira -> Codex -> GitHub -> deploy loop

Designing SDLC automation where AI summarizes tickets, starts work, manages Codex agents, creates PRs, supports human and AI review, updates Jira, and keeps stakeholders notified.

$ codex_101_enablement:

4 sessions standardized into reusable package

Converted Codex 101 delivery into a repeatable workshop system with live build, personalization, Plan Mode, deck generator, runbook, handouts, retro, and Jira workstream structure.

$ scientific_workflow_automation:

~80 hours saved per recurring batch

Enabled Staff Scientists with Codex + Python automation for Mass Spec workflows previously run manually.

$ engineering_productivity:

+30%

Productivity lift from DevEx standards + Codex enablement.

$ payments_products:

One Way to Pay, One Pay, Pay Over Time

Led delivery across customer-facing payment, wallet, and tender journeys at Walmart scale.

$ leadership_efficiency:

~35% productivity + contractor reduction

Scaled and optimized team mix at peak scope, saving hundreds of thousands annually in contract spend.

career.signal-map

Career Signal Map

Builder, Fintech Leader, AI Platform Operator

The story is not a pivot away from mobile and payments. It is the same operating discipline now applied to enterprise AI and DevEx at scale.

01

Foundation

Mobile engineer with production scars

Built Android and mobile commerce experiences before moving into management, so platform strategy still starts from how engineers actually ship.

  • Android delivery across grocery, checkout, pickup, search, favorites, and payment-adjacent journeys.
  • CI/CD, Appium, TestNG, Jenkins, analytics, and observability habits built before leadership scope expanded.
MobileFrontendReliabilityDevEx
02

Scale

Walmart payments and fintech movement

Led customer-critical payment programs through mobile, backend, risk, product, and legal alignment while scaling team ownership.

  • One Way to Pay, One Pay transition workstreams, Walmart EV Charging E2E, and multi-tender payment journeys.
  • Scaled from senior IC roots into senior manager scope across FTE and contractor delivery teams.
LeadershipPaymentsMobileBackend
03

Now

Enterprise AI operator and workshop lead

Administering and shaping OpenAI, Microsoft/GitHub Copilot, and Rovo adoption with practical workshops, scorecards, and reusable workflows.

  • Direct vendor partnership with OpenAI and Microsoft around enterprise tooling rollout and governance.
  • Codex admin enablement, golden prompts, AI scorecards, and hands-on rollout patterns for regulated engineering teams.
AI ToolingDevExPlatformLeadership

selected-work.md

Recent Work

Selected Builds and Enablement Systems

Production products and reusable enablement systems that show how I turn complex workflows into shipped, repeatable outcomes.

sentraia.dev, production domain, operational workflows

Sentra Residence live product

Built and operate a multi-role residential operations product for communities that replaces fragmented WhatsApp, spreadsheet, and guard-log workflows.

Evidence

  • Live public product presence at sentraia.dev with production access paths, domain identity, and a premium residential operations story.
  • Resident, guard, admin, and board workflows across QR access, packages, incidents, parking, announcements, reservations, finance, and moderation.
  • Supabase-backed synchronization, RLS-aware migrations, role-based routing, offline queueing, audit/logbook history, and mobile-first UX hardening.

Operating model

  • Product definition, PRD, backlog, executive summaries, and resident feedback templates.
  • Production web app plus Expo/React Native, Android Compose, iOS native, and Supabase tracks.
  • Device readiness guides, bug report template, GitHub publish checklist, and RN migration audit.
MobileFrontendBackendPlatformReliability
View Sentraia

101, 201, 301, and leaders tracks

Codex workshop curriculum

Turned workshop delivery into a reusable DevEx curriculum that grows from beginner-safe live builds into advanced agent operations, automation, and leadership rollout.

Evidence

  • Codex 101 captured under one reusable enablement model with Epic + 7 child workstreams.
  • Codex 201 expands into configurations, MCPs, skills, automations, multi-agent workflows, worktrees, and long-horizon tasks.
  • Codex 301 and leaders material extends the program into permissions, sandboxing, ExecRules, SDK/headless automation, harness engineering, governance, and rollout metrics.

Operating model

  • Treat workshop assets as products, not ad hoc slideware.
  • Offer different tracks for beginners, power users, platform engineers, and managers.
  • Keep Responsible AI, permissions, auditability, and measurement visible as the curriculum gets more advanced.
AI ToolingDevExPlatformLeadership

Measurement system, domain enablement, manual-hour reduction

AI productivity scorecard and scientific automation

Built the measurement and enablement layer that helps leaders separate real AI productivity gains from novelty usage.

Evidence

  • Designed and coded an OPEX AI scorecard to track adoption, productivity signals, and confidence bands across engineering workflows.
  • Enabled Staff Scientist partners to turn Mass Spec file handling across SQLite, CSV, TXT, and PDF inputs into Codex-assisted Python tooling.
  • Documented outcomes including roughly 60-80 manual hours saved across recurring sample workflows and stronger repeatability for regulated review.

Operating model

  • Measure usage, productivity, manual hours saved, confidence level, and operational risk instead of reporting licenses alone.
  • Pair domain experts with reusable prompts, validation checks, and traceable outputs.
  • Use scorecards to guide rollout, not to create vanity metrics.
AI ToolingDevExPlatformReliabilityLeadership

Jira, Rovo, Codex, GitHub, review, deployment, updates

Software development lifecycle automation

Building the operating model for an AI-assisted developer day: start with ticket intelligence, move into agent-assisted implementation, produce PRs, review with humans and Codex, merge safely, support deployment, and update work systems automatically.

Evidence

  • Validated ChatGPT + Atlassian Rovo patterns for Jira create, search, update, summarize, notification, and escalation flows under existing user permissions.
  • Connected the workflow concept to Codex agent delegation, GitHub PR creation, peer review, AI code review, and deployment handoff patterns.
  • Proved the pattern through a regulated workflow automation spike, then generalized it beyond a single use case into reusable software delivery automation.

Operating model

  • Create central templates for Jira summaries, daily developer briefings, issue updates, PR handoffs, review checklists, and deployment notes.
  • Keep humans in control at key gates: prioritization, code review, merge approval, release decision, and incident-sensitive updates.
  • Measure speed and quality through ticket cycle time, PR throughput, time to first working change, review latency, reopened work, and stakeholder notification reliability.
AI ToolingDevExPlatformReliabilityLeadership
Evidence DashboardA compact metrics layer for payments scale, leadership scope, SDLC automation, AI productivity, and manual-hour reduction.Open

impact.dashboard

Evidence Dashboard

Walmart Payments Scale

Mobile + backend

Customer-critical fintech-adjacent delivery

Scope

Android IC work on Walmart grocery and payment-adjacent journeys

Evidence

One Way to Pay, One Pay, Pay Over Time, EBT, Walmart Cash, Gift Cards, and EV Charging

payments platform scopeConfidence: Measured

Source: Walmart mobile payments leadership history. 2017-2026 Walmart Global Tech and Walmart Labs.

Leads with the Silicon Valley/Walmart chapter before the newer AI enablement layer.

Walmart Leadership Scale

10 FTE + 15 contractors

~35% productivity improvement

Scope

Senior IC into EM scope

Evidence

Peak Walmart payments org with optimized team mix

team operating scopeConfidence: Measured

Source: Leadership scope history. Walmart payments leadership.

Keeps the AI/DevEx story anchored in real people leadership and customer-critical delivery history.

SDLC Automation

Jira -> Codex -> GitHub

Developer-day workflow automation

Scope

Manual ticket triage, status updates, PR handoffs, and reminders

Evidence

Daily ticket summaries, Jira actions, Codex agents, PR creation, AI review, deployment handoffs, and automated updates

AI-assisted delivery loopConfidence: Proxy Signal

Source: ChatGPT + Rovo, Codex, and GitHub workflow assessment. April 2026 platform enablement direction.

A regulated workflow spike becomes one proof point inside a larger SDLC automation model for engineering teams.

AI Productivity Scorecard

+30%

Productivity lift tracked with confidence bands

Scope

Fragmented productivity claims

Evidence

Measured, proxy, and estimated signals in one scorecard

adoption + productivity signalConfidence: Measured

Source: OPEX AI adoption scorecard. Current DevEx platform work.

Keeps AI impact grounded in adoption, manual hours saved, confidence level, and operational risk.

Scientific Workflow Automation

~60-80 hours

Manual effort removed from recurring batches

Scope

Manual SQLite, CSV, TXT, and PDF handling

Evidence

Codex-assisted Python tooling with validation and traceability

manual hours savedConfidence: Estimated

Source: Staff Scientist enablement work. Recurring Mass Spec sample workflows.

The value is concrete enough for recruiters while still honest about confidence level.

Thermo Fisher AI Enablement

Codex Admin + Curriculum

Enterprise enablement system expanded

Scope

Admin/operator responsibility and foundation workshop package

Evidence

Beginner, advanced, automation, and leadership tracks with rollout guardrails

Codex admin enablement systemConfidence: Measured

Source: Thermo Fisher Codex admin/operator work plus 101, 201, 301, and leaders decks. March-April 2026 workshop roadmap.

Frames workshops as one mechanism inside a broader AI enablement and governance role.

Architecture ViewsSystem diagrams for the AI-assisted SDLC loop, rollout guardrails, and production product ownership model.Open

architecture-views.md

Architecture Views

System diagrams for reviewers who want to see how the work actually moves.

AI-assisted SDLC loop

How a developer moves from ticket context to shipped work with humans still owning the important decisions.

  1. 01

    Jira intelligence

    Daily ticket briefings, priority context, issue creation, search, updates, notifications, and escalations.

  2. 02

    Codex planning

    Plan Mode, repo context, constraints, tests, worktrees, and agent-managed subtasks.

  3. 03

    GitHub PR flow

    Implementation branches, PR creation, peer review handoff, AI review support, and CI feedback.

  4. 04

    Human gates

    Engineer and peer approval for code review, merge, release, and incident-sensitive changes.

  5. 05

    Work-item updates

    Jira summaries, status changes, deployment notes, and stakeholder notifications after the work moves.

Enterprise AI rollout model

How AI tooling becomes a platform capability instead of a scattered license rollout.

  1. 01

    Admin controls

    Least privilege, approved tools, permission boundaries, and explicit approval prompts.

  2. 02

    Enablement

    Codex 101, 201, 301, leaders sessions, golden prompts, runbooks, and office hours.

  3. 03

    Measurement

    Usage quality, task depth, PR throughput, manual hours saved, confidence bands, and developer sentiment.

  4. 04

    Guardrails

    Responsible AI framing, review expectations, policy alignment, and reusable workflow templates.

Production product ownership

How the personal production system proves hands-on judgment beyond enterprise leadership claims.

  1. 01

    Product discovery

    Residents, guards, admins, board members, QR access, packages, incidents, parking, announcements, and finance workflows.

  2. 02

    Platform build

    Next.js, Expo/React Native, Supabase, RLS-aware migrations, role routes, offline queues, and audit logs.

  3. 03

    Mobile readiness

    QR scanning, package photos, persisted auth, push readiness, account lifecycle, release profiles, and device checks.

  4. 04

    Operations

    Feedback templates, readiness checklists, migration audits, release notes, and real workflow hardening.

leadership.scope

Leadership Scope Growth

Initial EM promotion

Stage 1 - Engineering Manager Scope

4 peer engineers (2 iOS, 2 Android)

Wins

  • Established execution rhythm and delivery ownership in mobile payments.
  • Built a strong technical baseline for cross-platform payment features.

Outcomes

  • Created high-trust operating cadence that enabled rapid expansion.
  • Prepared team for higher-complexity, cross-functional programs.

Post major delivery wins

Stage 2 - Senior Manager Expansion

8 FTE + 10 contractors

Wins

  • Delivered Walmart EV Charging E2E and Walmart Pay One Way to Pay.
  • Led One Pay migration from legacy Capital One flow with business/legal alignment.

Outcomes

  • Supported multimillion-dollar payment-flow impact.
  • Improved cross-team predictability and reduced release risk.

Peak scope period

Stage 3 - Peak Organization Optimization

10 FTE + 15 contractors (peak), then contractor reduction

Wins

  • Set explicit leadership goals tied to velocity and quality.
  • Empowered full-time engineers to own more critical implementation paths.

Outcomes

  • ~35% productivity improvement across delivery streams.
  • Saved hundreds of thousands in annual contract expenditure.
Enterprise AI Enablement and Codex AdminCodex 101/201/301 plus manager enablement, packaged as a reusable enterprise AI adoption system.Open

workshops.enablement

Enablement System

Enterprise AI Enablement and Codex Admin

Practical sessions for teams that need AI adoption to survive real repositories, regulated constraints, and production delivery.

Thermo Fisher Codex admin/operator context

Codex 101 Enablement System

Delivered foundation track

A beginner-safe workshop system built around blank-folder setup, first build, personalization, Plan Mode, recap, and Q&A.

Audience

New Codex users across engineering-adjacent teams

Outcomes

  • Standardize first-use guidance with reusable deck, deck generator, attendee prompt, speaker notes, and facilitator runbook.
  • Teach build, personalize, plan, polish, and verify as the durable workflow.
  • Capture delivery work as a reusable Epic and workstream model instead of one-off session noise.
CodexNext.jsRunbooksJira

Codex 201 Advanced Workflows

Upcoming April 23, 2026

A second-level workshop covering how Codex becomes a team operating model through configurations, MCPs, skills, automations, worktrees, multi-agent flows, and long-running task structure.

Audience

Developers and teams ready to move from prompts into repeatable agent operations

Outcomes

  • Teach secure-by-default setup across approval mode, sandbox mode, model defaults, and shared configuration.
  • Show how MCPs, skills, and automations reduce copy-paste context and encode team best practices.
  • Introduce parallel workflows, worktrees, and long-horizon task patterns for larger engineering efforts.
CodexMCPSkillsAutomationsWorktrees

Codex 301 Advanced Features and Automations

Upcoming April 30, 2026

A deeper technical session on permissions, sub-agents, Plan Mode, personality, memory, Windows sandboxing, status line, writable roots, ExecRules, SDK/headless execution, CI automation, and harness engineering.

Audience

Power users and platform engineers designing safe agent workflows at scale

Outcomes

  • Explain how sandboxing, approvals, ExecRules, and writable roots keep advanced usage controlled.
  • Show how SDK/headless mode can power security triage, test coverage bots, CI auto-fix, release hygiene, and issue labeling.
  • Teach teams to make products legible to agents through repo knowledge, observability, worktrees, and enforceable guardrails.
CodexExecRulesSDKCI botsHarness Engineering

Codex for Leaders

Manager-focused leadership session

A leadership track for operating the AI-native engineering organization: why Codex changes the SDLC, how to govern rollout, how to build champions, and how to measure adoption, quality, and delivery speed together.

Audience

Engineering managers, senior leaders, and transformation owners

Outcomes

  • Frame Codex as an operating model shift from code completion to agentic delegation.
  • Help leaders plan governance, RBAC, auditability, security controls, champions, and rollout sequencing.
  • Teach metrics that avoid vanity reporting: weekly active use, task depth, code quality, PR throughput, time to merge, developer satisfaction, and hours saved.
CodexLeadershipGovernanceMetricsRollout

Codex for Real Repositories

90-minute hands-on workshop

Teams bring real tickets, repo context, and test expectations, then learn a repeatable Codex workflow for implementation, debugging, review, and Plan Mode refinement.

Audience

Engineers, tech leads, and managers adopting AI in active codebases

Outcomes

  • Turn ambiguous tickets into scoped implementation plans.
  • Use repository context, tests, and constraints to recover from weak first-pass results.
  • Leave with a team-ready prompt pattern, review checklist, and confidence-building workflow.
CodexOpenAIGitHubCI/CD

Enterprise AI Tooling Admin Playbook

60-minute operating model session

A practical admin view of OpenAI, Microsoft/GitHub Copilot, and Rovo adoption across permissions, onboarding, governance, and measurement.

Audience

Platform, DevEx, and engineering leadership teams

Outcomes

  • Define rollout guardrails without blocking developer flow.
  • Map least-privilege access, auditability, and usage measurement.
  • Identify adoption signals beyond license activation.
OpenAIMicrosoftGitHub CopilotRovo

DevEx Metrics Lab

Working session with scorecard template

Turns fuzzy productivity claims into measurable signals across onboarding, build time, CI reliability, flaky tests, AI usage, and manual hours saved.

Audience

Teams trying to prove platform and AI adoption impact

Outcomes

  • Create a scorecard with measured, proxy, and estimated confidence bands.
  • Choose metrics that drive behavior instead of vanity reporting.
  • Build a rollout plan for incremental adoption.
ScorecardsCI/CDAnalyticsAI Tooling
Voice of ImpactSelected impact quotes and outcome signals for leadership, delivery, and enablement credibility.Open

impact.voices

Voice of Impact

Codex CLI + GitLab on active .NET codebase

“Codex became the most effective code assistant in our delivery flow once we integrated it through CLI into the real repo context.”

Senior Engineer, Internal Product Team

  • Added unit tests for a class that previously had no test coverage.
  • Renamed class and namespace safely in a production codebase.
  • Implemented an entire Jira ticket in about 1 hour vs ~2 day estimate.
  • Recovered from first-pass failure by adding richer context and codebase constraints.
AI ToolingDevExBackend

Clinical mass spectrometry tooling enablement

“Codex helped translate expert lab know-how into production-grade internal tools without heavy engineering overhead.”

Staff Scientist Partner, Thermo Fisher

  • Built 3 internal apps in days with Codex + Python support.
  • Reduced one manual collection workflow from ~30 minutes to ~5 minutes.
  • Automated review/report preparation that was costing ~15-20 minutes per sample.
  • Unlocked an estimated ~60-80 manual hours saved across ~500 recurring samples.
AI ToolingPlatformDevExReliability
Leadership PlaybookThe operating habits behind team design, execution cadence, quality gates, incidents, hiring, and coaching.Open

leadership.playbook

Leadership Playbook

Execution Cadence

Reliable execution starts with clear operating rhythm and decision quality.

  • Weekly operating review linking roadmap, delivery confidence, and risk.
  • Monthly architecture checkpoints for cross-team dependencies and tradeoffs.
  • Visible KPI scorecard (velocity, reliability, AI adoption, team health).
  • Codified delivery ownership map so each stream has explicit decision accountability.

Incident Model

Incidents are run as leadership exercises, not just technical drills.

  • Defined severity model, escalation paths, and response ownership.
  • Blameless postmortems with concrete remediation and recurrence guardrails.
  • Readiness practice across product, engineering, and support stakeholders.
  • Rotating incident command model with postmortem governance reviews at leadership level.

Hiring and Coaching

High-performing teams are built through deliberate talent systems.

  • Structured interview loops with role-level scorecards and calibration.
  • Manager + senior engineer coaching plans tied to measurable growth goals.
  • Promotion-readiness framework focused on scope, impact, and influence.
  • Calibration checkpoints to align promotions, growth plans, and succession readiness.

experience.log

Experience Timeline

Timeline Mode

  1. Thermo Fisher Scientific

    Staff Engineer - Developer Experience

    Jan 2026 - Present

    • Drove developer productivity strategy across CI/CD standards, automation, and platform engineering practices.

      LeadershipDevExPlatform

    • Implemented Codex-enabled workflows and playbooks that contributed to over 30% engineering productivity improvement.

      AI ToolingDevExLeadership

    • Established reusable golden-path templates for services and pipelines to improve onboarding and consistency.

      DevExPlatformBackend

    • Strengthened reliability through release guardrails, automated checks, and clearer operational ownership.

      ReliabilityPlatformDevEx

    • Partnered with engineering leaders to align platform investments to measurable team outcomes.

      LeadershipPlatform

  2. Walmart Global Tech

    Senior Engineering Manager II - Payments

    Sunnyvale, California

    Sep 2022 - Jan 2026

    • Drove key wins including Walmart EV Charging E2E and Walmart Pay One Way to Pay across EBT, Walmart Cash, Gift Cards, and additional tenders.

      LeadershipPaymentsMobileBackend

    • Scaled organization scope to 8 FTE + 10 contractors across critical mobile and backend payment programs.

      LeadershipPlatform

    • Acted as technical lead for One Way to Pay implementations that supported multimillion-dollar revenue impact.

      LeadershipPaymentsBackend

    • Led migration from legacy credit-card program flow to One Pay under business and legal constraint alignment.

      PaymentsBackendReliability

    • At peak scope led 10 FTE + 15 contractors, improved productivity by ~35%, and reduced contractor dependence to save hundreds of thousands annually.

      LeadershipPlatform

  3. Walmart Global Tech

    Senior Engineering Manager - Payments

    Sunnyvale, California

    Mar 2021 - Sep 2022

    • Promoted from senior IC track into management and led a pod of 4 peers (2 iOS, 2 Android).

      LeadershipMobile

    • Established execution cadence, engineering standards, and release governance for high-visibility payment workstreams.

      LeadershipReliabilityPlatform

    • Drove architecture alignment across mobile and services for scalable wallet and tender orchestration.

      PaymentsMobileBackend

    • Built cross-functional trust model with product and architecture leaders to accelerate critical program decisions.

      LeadershipPlatform

  4. Walmart Global Tech

    Senior Mobile Engineer

    San Francisco Bay Area

    Jun 2018 - Mar 2021

    • Designed and delivered core grocery app flows across pickup, check-in, checkout, delivery, favorites, search, and payments.

      MobilePaymentsFrontend

    • Built on a high-scale, multi-tenant commerce platform with Java, Kotlin, React Native, and backend integrations.

      MobileBackendReliability

    • Implemented analytics instrumentation and observability to improve product decisions and production debugging.

      MobileBackendReliability

    • Strengthened quality with CI/CD pipelines, test automation, and TDD practices using Jenkins, Maven, TestNG, and Appium.

      DevExMobilePlatform

  5. Walmart Labs

    Android Engineer (Contract)

    Sunnyvale, California

    Aug 2017 - Jun 2018

    • Delivered Android capabilities for Walmart Grocery app flows and payment-adjacent customer journeys.

      MobilePaymentsFrontend

    • Implemented production fixes and performance improvements in a large-scale mobile commerce platform.

      MobileReliability

    • Automated regression coverage and improved release confidence through mobile test tooling.

      DevExMobileReliability

    • Collaborated across product, QA, and platform teams to ship on tight timelines.

      LeadershipMobile

  6. Hexaware Technologies

    Associate System Engineer

    Saltillo, Coahuila, Mexico

    Mar 2017 - Aug 2017

    • Contributed to enterprise software implementation and support for client-facing systems.

      BackendReliability

    • Improved delivery quality through defect triage, issue resolution, and structured handoffs.

      ReliabilityPlatform

    • Collaborated with cross-functional stakeholders to align requirements and technical execution.

      LeadershipBackend

    • Strengthened foundational engineering practices for scalable software delivery.

      PlatformDevEx

  7. G&G Ingenieria E Innovacion Tecnologica

    Jr Android Engineer

    Queretaro, Mexico

    Nov 2013 - Aug 2016

    • Implemented native Android applications based on client designs with strong deadline discipline.

      MobileFrontend

    • Supported QA and automation efforts to improve release stability and product quality.

      MobileReliabilityDevEx

    • Tracked and resolved defects through structured ticket workflows and close team collaboration.

      ReliabilityPlatform

    • Built core engineering fundamentals that later scaled into leadership and platform ownership roles.

      LeadershipMobile

skills.matrix

Skills Matrix

LevelMobilePayments/FintechBackendFrontendPlatform/DevExAI Tooling
ExpertAndroid ArchitecturePayment Orchestration / Wallet and Tender Systems--CI/CD and Golden Paths / Developer Productivity Programs / Workshop ProductizationCodex Enablement
StrongKotlin + Jetpack Compose Direction / Expo / React Native Delivery / Mobile Platform Reliability / iOS Delivery CollaborationCredit / Pay Over Time Migration / Risk and ControlsService Architecture / API and Event Integrations / Supabase + RLS Workflows / Distributed OperationsNext.js + TypeScript / Product Delivery Alignment / UX and Accessibility ReviewsInternal Platform StandardsOpenAI / Copilot / Rovo Administration / AI Adoption Scorecards / AI-assisted Engineering Workflows / Prompt and Tooling Strategy
Familiar---Design System Partnerships--
GitHub ActivityPublic repository activity plus curated private-work artifacts that GitHub cannot show directly.Open

github.activity

GitHub Activity

Recent repositories and contribution blocks, including private-work approximation.

GitHub Profile

Repository activity is temporarily unavailable. Verify GitHub username or wait for API limits to reset.

Selected Engineering Artifacts

Curated proof from private, enterprise, and workshop work that public GitHub activity cannot show directly.

Codex Workshop Materials

Progressive workshop curriculum across Codex 101, 201, 301, and leaders sessions with decks, runbooks, prompts, live workflows, and rollout guidance.

AI ToolingDevExPlatform

DevEx Golden Path Templates

Reusable standards for CI/CD, onboarding, quality gates, and safe AI-assisted engineering adoption.

DevExReliabilityPlatform

Enterprise SDLC Automation Assessment

Prioritized ChatGPT/Rovo, Codex, GitHub, PR review, deployment, and work-item automation opportunities across business value, feasibility, enterprise readiness, risk, complexity, and dependencies.

AI ToolingDevExPlatformReliability
Case StudiesDetailed case studies for Walmart payments, DevEx, scientific automation, SDLC automation, and Sentra Residence.Open

case-studies.md

Case Studies

Payments at Walmart

One Way to Pay, One Pay transition, and multimethod checkout scale

Expand
LeadershipPaymentsMobileBackendReliability

Problem

Walmart needed to launch and evolve modern payment experiences while maintaining reliability, trust, and execution speed.

Constraints

  • Large customer scale with strict uptime and performance expectations.
  • Cross-functional dependencies across mobile, backend, risk, and product organizations.
  • Business and legal constraints during migration from legacy card-program flow to One Pay ecosystem direction.

Approach

  • Created clear ownership and operating cadence across teams and technical domains.
  • Aligned architecture around resilient payment flows, observability, and graceful failure handling across One Way to Pay.
  • Drove iterative launches with disciplined release controls and customer-impact monitoring.

Results

  • Delivered major programs including Walmart EV Charging E2E, One Way to Pay, and One Pay migration enablement workstreams.
  • Improved delivery confidence through stronger reliability guardrails and incident readiness.

Lessons

  • Payments leadership requires both technical rigor and tight cross-team execution alignment.
  • Customer trust scales when product velocity and reliability discipline are treated as co-equal goals.

DevEx at Thermo Fisher

Codex adoption and platform standards for engineering velocity

Expand
LeadershipDevExAI ToolingPlatformReliability

Problem

Engineering teams needed a consistent, low-friction way to ship quality software faster without increasing operational risk.

Constraints

  • Tooling and workflow fragmentation across repositories and teams.
  • Need to increase throughput while keeping reliability and governance intact.
  • Adoption had to be practical for teams with different maturity levels.

Approach

  • Defined standard CI/CD templates and implementation playbooks for common engineering workflows.
  • Integrated Codex-assisted patterns for repetitive tasks, documentation, and troubleshooting.
  • Introduced adoption support, feedback loops, and measurable outcome tracking for teams.

Results

  • Realized more than 30% engineering productivity improvement through DevEx + AI tooling enablement.
  • Reduced delivery friction and improved consistency across planning, implementation, and release activities.

Lessons

  • Developer experience gains are durable when standards are easy to adopt and clearly measurable.
  • AI tooling delivers the most value when embedded into everyday workflows, not treated as side experiments.

AI-enabled Scientific Workflow Automation

Codex + Python enablement with Staff Scientist partners

Expand
AI ToolingPlatformDevExReliabilityLeadership

Problem

Mass spectrometry data processing required manual extraction and parsing across SQLite, CSV, TXT, and PDF files, creating delays and avoidable errors.

Constraints

  • Regulated workflow expectations with traceability and compliance requirements.
  • Domain logic lived with subject-matter experts, not in repeatable tooling.
  • Manual cycle was consuming roughly 80 hours per recurring batch.

Approach

  • Partnered directly with Staff Scientists to encode lab-domain logic into Codex-assisted Python tooling.
  • Implemented automated delta analysis, QC threshold checks, and structured validation steps.
  • Automated reporting outputs and operational traceability fields (work order, instrument, operator attribution).

Results

  • Moved from ~20 minutes per sample manual handling to near-instant processing flows for key steps.
  • Reduced recurring manual effort by approximately 80 hours per batch while improving consistency.

Lessons

  • AI adoption scales fastest when enablement is paired with domain experts and measurable outcome tracking.
  • Codex value compounds when DevEx provides reusable patterns, guardrails, and coaching.

Software Development Lifecycle Automation

Jira intelligence, Codex agents, GitHub PRs, review, deployment, and work-item updates

Expand
AI ToolingDevExPlatformReliabilityLeadership

Problem

Developers lose time across the seams of the SDLC: finding ticket context, summarizing priorities, creating implementation plans, opening PRs, coordinating reviews, updating Jira, and keeping stakeholders informed.

Constraints

  • Connector actions need to respect existing user permissions and explicit approvals before changing Jira or GitHub state.
  • Automation must preserve human ownership around prioritization, code review, merge, deployment, and incident-sensitive communication.
  • The workflow has to scale through templates and guardrails instead of one-off automations owned by a single person.

Approach

  • Validated ChatGPT + Atlassian Rovo flows for Jira create, search, update, summarize, notification, and escalation patterns.
  • Designed the end-to-end developer-day loop: AI ticket briefing, Codex planning, agent-managed implementation, GitHub PR creation, human peer review, Codex code review, merge/deployment handoff, and automatic Jira updates.
  • Assessed connector opportunities using business value, feasibility, enterprise readiness, risk, complexity, and dependencies.

Results

  • Shifted the story from isolated connector demos to a governed SDLC automation model that can improve developer speed and consistency.
  • Defined reusable workflow patterns for ticket summaries, Jira actions, PR handoffs, AI reviews, notifications, escalations, and deployment updates.
  • Used regulated workflow automation as a concrete proof point while making the broader value clear for engineering teams.

Lessons

  • The biggest productivity gain is not only code generation; it is reducing handoff friction across the entire software delivery lifecycle.
  • The best DevEx systems are central enough to scale, local enough for teams to tailor, and explicit enough for enterprise governance.

Sentra Residence / Privada Reforma

Live residential operations product across web, mobile, and Supabase

Expand
LeadershipMobileFrontendBackendPlatformAI ToolingReliability

Problem

Residential communities need to replace fragmented WhatsApp, spreadsheet, guard-log, and legacy app workflows with one operational system.

Constraints

  • Built and operated by a single engineer with broad resident, guard, admin, and board scope.
  • Needed production reliability for access, packages, incidents, parking, announcements, reservations, finance, and moderation.
  • Required a public product domain, web, React Native, native mobile, and Supabase tracks to evolve without losing auditability, device readiness, or role boundaries.

Approach

  • Launched a public product presence at sentraia.dev to frame the platform as a real residential operations product, not only a private app.
  • Built the production web platform with React 19, TypeScript, Vite, Supabase migrations, RLS-aware workflows, and reusable domain primitives.
  • Created deterministic QR access, guard manual validation, delivery authorization, offline queueing, package photo workflows, audit logs, and bilingual UX.

Results

  • Shipped a real production personal product with its own domain and access path, replacing fragmented daily operations with a role-aware system.
  • Documented PRDs, executive summaries, resident feedback templates, migration audits, test readiness, and release checklists to keep the work reproducible.
  • Demonstrated end-to-end ownership across product discovery, architecture, implementation, QA, mobile migration, and operational hardening.

Lessons

  • A personal production product is the best proof of full-stack judgment because edge cases arrive from real users, not imagined requirements.
  • AI acceleration is safest when paired with explicit docs, migrations, test readiness, and operational guardrails.
Evidence Available On RequestA recruiter-safe index of private, enterprise, workshop, and product artifacts that can be discussed selectively.Open

evidence-vault.md

Evidence Available On Request

A public-safe index of private, enterprise, workshop, and production artifacts I can discuss selectively.

AI enablement assets

Workshop systems and operating documents that can be discussed or shown selectively.

Expand

Examples

  • Codex 101 / 201 / 301 decks
  • Codex for Leaders materials
  • golden prompt libraries
  • facilitator runbooks

SDLC automation artifacts

Workflow patterns for turning Jira, Rovo, Codex, and GitHub into a governed developer-day loop.

Expand

Examples

  • daily ticket briefing template
  • Jira action patterns
  • PR handoff checklist
  • AI review checklist
  • deployment update template

Measurement systems

Scorecards that connect AI adoption and platform work to measurable outcomes.

Expand

Examples

  • AI productivity scorecard
  • manual-hours-saved tracking
  • confidence bands
  • risk and readiness scoring

Production build proof

Architecture and delivery artifacts from shipped personal product work.

Expand

Examples

  • Privada Reforma PRD
  • role-based architecture notes
  • mobile readiness guide
  • release checklist
  • migration audit

Leadership operating docs

Patterns from managing teams through scale, payments delivery, and org optimization.

Expand

Examples

  • operating review cadence
  • incident readiness model
  • team ownership maps
  • promotion and coaching frameworks

conversation-starters.md

Good Reasons To Talk

The page is intentionally built around the conversations where I can create the most leverage.

You need a leader who understands mobile payments and implementation risk.

Talk to me about Walmart-scale checkout, wallet/tender orchestration, Android delivery, and release confidence.

You want DevEx automation across Jira, PRs, reviews, deployment, and updates.

Talk to me about reducing handoff friction, building templates, measuring cycle time, and making agents useful to teams.

You need AI adoption to survive real repos, permissions, and auditability.

Talk to me about Codex/Rovo/GitHub workflows, admin controls, rollout metrics, and where humans should stay in the loop.

You need someone who can manage teams and still reason through architecture.

Talk to me about operating cadence, coaching senior engineers, incident models, platform trade-offs, and adoption at scale.

Book a CallEmail

contact.sh

Let's Build the Next Platform Win

Open to Senior Manager and senior leadership conversations where business outcomes, engineering rigor, and team growth are all first-class priorities.

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marcodiaz04@icloud.commarco.diaz@thermofisher.com