ai systems builder · tier-1 regulated financial services

Muhil.

AI Systems Builder. Fifteen years architecting and shipping enterprise AI/ML platforms inside regulated environments. Spec-driven delivery, agentic CI/CD, responsible AI as a first-class engineering concern.

what i build

Agentic AI systems & platforms that take work from spec to production in days — with safety, audit and explainability built into the build, not the release.

agenticspec-drivenregulated
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years engineering AI/ML platforms in regulated environments

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AI-SDLC tooling adoption across the teams I lead

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senior AI/architecture roles across two decades

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faster — multi-sprint features compressed to multi-day releases

01 · The brief

Architecture is what you draw. Building is what survives Monday.

Ihave spent fifteen years designing, building and scaling enterprise AI/ML platforms inside regulated environments. I lead advanced AI engineering teams delivering the full model lifecycle — experimentation, training, deployment, governance, production operations — and the agentic tooling that drives them.

The job isn't to draw boxes. It is to run a disciplined path from emerging-technology evaluation through PoC, MVP, investment case and production at scale — then to change how the team works while doing it. I have hit 100% adoption of AI-SDLC tooling across the teams I lead, and compressed multi-sprint features to multi-day production releases. No loss of quality. No loss of governance rigour.

I act as a trusted advisor to CIO, CTO, CPO and Data & AI engineering leadership — shaping firmwide GenAI, Agentic AI and platform strategy at enterprise scale.

My position is straightforward: AI changes how we build, not just what. Spec-driven, continuous flow. Agentic CI/CD. Responsible AI as a first-class engineering concern. Builders > architects who don't build.

02 · The position

AI doesn't just change what we ship. It changes how.

01
Architects who don't build are unreliable narrators.

The drawing should survive Monday. Mine ships — to production, in regulated environments, on real customer load.

02
Spec-driven beats sprint-driven inside a regulated environment.

The team that ships every three days governs better than the one that ships every six weeks. Cadence is a control, not a constraint.

03
Governance is a build dependency, not a release gate.

AI safety, audit, explainability — first-class engineering concerns, left of the deploy. Compliance is something the platform does, not something it asks you to do.

03 · The stack

Five layers,
one operating system.

The reference architecture under every AI system I ship at scale. Hover any layer to expand its current inventory.

Experience

L1 · engineers · analysts · business users
MDLC AssistantBI AssistantAI OrchestratorSpec→DeployInternal APIs

Agents

L2 · task · review · governance
GitHub CopilotClaude CodeCursorCustom Agentic CI/CDSpec interpreter

Platform

L3 · models · rag · multi-tenancy
LLMSuiteAI GatewayModels-as-a-ServiceVector store · RAG1,200+ → ~40 accounts

Governance

L4 · safety · reliability · audit
AI SafetyReliabilityAudit + traceExplainabilityModel governance

Foundation

L5 · aws bedrock · serverless · iac
AWS BedrockCloudFormationEvent-driven archObservabilityIdentity · IAM

04 · Track record

$ git log --oneline --since=2011

Fifteen years of shipped systems. Each commit is what actually moved.

a4f12c HEAD → main
Head of AI Platform Services & Chief Architect
(jpmc/ai-platform-services)  JPMorgan Chase · Glasgow
+14-person AI eng team built ground-up
+MDLC Assistant + BI Assistant (conversational AI in prod)
+AI Orchestrator (identity brokering · self-service MLOps · agentic interface)
+3 major releases at pace
+100% Copilot/Claude Code/Cursor adoption
−Scrum sprints
Dec 2025 → now
c8e09a
Chief Architect — Firmwide AI/ML Platform
(jpmc/ml-platform)  JPMorgan Chase · Glasgow
+Models-as-a-Service on AWS Bedrock
+LLMSuite + AI Gateway (multi-tenant)
+1,200+ AWS accounts consolidated to ~40
+Responsible AI governance firmwide
+PoC → prototype → investment → production discipline
Jun 2023 → Dec 2025
71b3df
Executive Director · Principal Architect, OmniAI & ML Services
(jpmc/omniai)  JPMorgan Chase · Glasgow
+OmniAI training/experimentation platform
+firmwide architectural standards
+technical governance frameworks
Aug 2021 → Jun 2023
19a740
Technical Lead → Senior Solutions Architect
(cirrushq/tda)  CirrusHQ · Scotland
+Founded Technical Design Authority
+Partnered directly with CEO/CTO on strategy
+IaC/CodePipeline/CloudFormation org-wide
+AWS Education Competency
May 2015 → Aug 2021
0091cf
Web Developer & Systems Administrator
(accent/init)  Accent Design Group
+AWS migration
+custom CMS for regulated sectors
+first commit
Sep 2011 → May 2015
05 · Case study

Two sprints versus three days.

What changed when the team moved from Scrum cadence to spec-driven continuous flow. Toggle to compare.

Delivery comparison
3 days, agentic flow
0d
1d
2d
3d
spec authored + reviewed
agent kickoff
first PR
agentic CI · auto-review
governance pass
production ✓
planbuildreviewship
Spec authored, not ticketed

Intent + acceptance criteria + governance scope written once. Agents and engineers work the same artefact.

Agentic CI runs review

Copilot + Claude Code drive PRs; auto-review covers style, security and contract. Humans approve substance.

Governance moves left

AI safety, audit and explainability are checks on the build, not the release. Cadence stays continuous.

·  on the work  ·

"Within thirty days the team had stopped arguing about adoption and started arguing about what to build next."
NMV retrospective February 2026

Get in
touch.

Advisory

CIO/CTO/CPO-level advisory on AI platform strategy, governance and AI-SDLC adoption — emerging-technology evaluation through to production at scale.

Email me directly →
Speaking

Keynotes & panels on agentic systems, responsible AI, spec-driven delivery and engineering culture transformation.

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