Cloud + AI systems architect

I turn complex technology into systems that move.

Senior cloud application architect with 28+ years of hands-on experience designing enterprise platforms, practical AI systems, and automation that teams can operate at scale.

View selected work Explore experience
Cloud architectureAI engineeringAutomation
ENTERPRISE SCALE
ARCHITECTCloud-native
systems
01AI
02DATA
03AUTOMATION
BUILDING FOR OUTCOMES
28+Years building
enterprise systems
800M+Documents migrated
in a major platform
100+Applications supported
through cutover
10/10Customer satisfaction
on AWS engagements
01 / Experience

Architecture leadership,
grounded in delivery.

Leading enterprise cloud transformation across financial services, insurance, automotive, aviation, fintech, and consumer industries.

Current

Senior Cloud Application Architect

AWS Professional Services

Lead enterprise cloud-native application programs from architecture and implementation through operational readiness and production adoption. Build reusable patterns across cloud platforms, distributed systems, AI, and governance.

28+ years

Engineering & Architecture Leadership

Enterprise technology

Hands-on leadership across application platforms, integration, data, APIs, serverless systems, and large-scale modernization—connecting executive outcomes with engineering reality.

02 / Selected case studies

Built for the hard parts.

Selected programs where architecture, engineering, and measurable outcomes came together.

01

Cloud architecture · Data platforms

A document platform built for extraordinary scale

Led the architecture and delivery of a cloud-native migration for a mission-critical enterprise document platform while supporting a complex application cutover.

Amazon S3AWS LambdaDynamoDBOpenSearchSpring Boot
800M+ documents100+ applicationsSub-second retrieval
02

AI engineering · Transformation

Agentic automation that compressed assessment cycles

Designed AI-assisted assessment flows to analyze a large application and server estate, surface modernization pathways, and keep recommendations reviewable through governance controls.

Agentic workflowsRAGHuman reviewAWSEvaluation
800+ applications3,000+ serversWeeks → days
03

Automation · Authorization

Policy as code that teams could adopt quickly

Created a reusable policy-based authorization framework with a shared policy store, application middleware, and a Git-governed delivery path for consistent enterprise adoption.

CedarVerified PermissionsLambdaGitOpsPolicy testing
12 roles → 43 weeks → 2 days<5 min policy change
03 / Technical skills

Broad enough to see the system. Deep enough to build it.

A practical toolkit for moving from strategy to architecture, implementation, and reliable production operations.

01

Cloud & platforms

  • AWS
  • Serverless
  • Microservices
  • Containers
  • Multi-region architecture
  • API platforms
  • Data platforms
02

AI engineering

  • Agentic systems
  • RAG
  • LangGraph
  • Model evaluation
  • Prompt engineering
  • Knowledge bases
  • Human-in-the-loop
03

Engineering & automation

  • Java / Spring Boot
  • Python
  • TypeScript
  • Terraform
  • AWS CDK
  • CI/CD
  • Temporal
04

Governance & operations

  • Policy as code
  • AI governance
  • Observability
  • Security architecture
  • Resilience
  • Performance
  • Operational readiness
04 / Writing

Ideas from the field

Architecture,
made practical.

Notes on cloud architecture, enterprise AI, and the engineering patterns that turn ambitious systems into maintainable ones.

Explore all posts on Substack
01

Java · AWS Lambda · Architecture

Building Java AWS Lambda Functions with Hexagonal Architecture

A practical ports-and-adapters pattern for keeping Lambda handlers thin while integrating API Gateway, SQS, DynamoDB, S3, and external APIs.

Read article
02

Enterprise AI · Knowledge Architecture

Beyond Data Lakes: Building the Knowledge Layer for Enterprise AI Transformation

Why enterprise AI needs a governed knowledge layer that turns fragmented data and documents into usable, contextual organizational intelligence.

Read article
03

AI Agents · Software Engineering

From Developing Microservices to Building AI Agents

A practical layered approach that maps familiar backend engineering disciplines to agent applications, tools, retrieval, memory, and workflows.

Read article
05 / Contact

Complex challenge?
Let's make it clear.

I'm always interested in thoughtful conversations about cloud-native platforms, applied AI, architecture leadership, and automation at scale.

Based inAtlanta, Georgia
Emailmssanjay@gmail.comLinkedInConnect with me ↗RésuméDownload PDF ↓