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Core strengths

What I'm known for

The strengths I bring at scale, from applied AI and the data and distributed systems beneath it, to the identity foundations, the modernization and sourcing calls, and the leadership that holds it together.

Applied & Agentic AI

A large-scale context engine powering multi-agent LLM applications. Hybrid RAG, agentic pipelines, MLOps, and ML inside user-facing products, grounded and guardrailed throughout, with the evaluation and responsible-AI standards that let it ship.

Data Platforms

The governed data foundation analytics and AI run on. Fragmented estates consolidated into a single lakehouse, with real-time pipelines, metadata, lineage, and GDPR and CCPA compliance across millions of accounts.

Distributed Systems & Architecture

Large-scale multi-tenant SaaS designed from first principles: domain-driven microservices, micro-frontends, and mobile-first apps on the BFF pattern, over event-driven, cloud-native foundations built for peak load.

Engineering Leadership & Org Design

Building and scaling engineering organizations of 250 and up across web, mobile, backend and AI/ML, leading through directors and managers. I hire and grow the leaders who run the teams, shape squad and tribe structures to the outcome, and raise delivery predictability so commitments hold.

Identity & Access at Scale

My specialty: identity and access platforms built from the ground up. Real-time, cross-channel identity resolution proven at millions of concurrent profiles, consolidated onto OIDC and OAuth 2.0, with the security and privacy posture to match.

Modernization, Cloud & M&A Consolidation

Turning monoliths, legacy estates and acquired platforms into one modern system. Domain-driven microservices via the Strangler Fig pattern, zero-downtime cloud migrations worth more than $50M in operational and vendor savings, four authentication systems onto a single standard, and four business-unit data platforms into one lakehouse.

Sourcing & Capacity Strategy

Deciding what a company should own and what it should rent. I have brought product suites back in house from vendor operation, rebuilt the internal capability to run them, and used outsourcing and staff augmentation deliberately where speed or a temporary skill gap called for it, sized against the multi-year roadmap rather than the current quarter.

Executive Partnership & Governance

Owning P&Ls above $20M and multi-year roadmaps in regulated environments. I partner with product and business leaders, run vendor strategy and negotiation, mature governance and compliance, and translate engineering and AI complexity for C-suite and board audiences.

The stack

What I work with

Two decades of accumulated stack, ordered the way the rest of this page runs: leadership at the top, the code at the bottom. Everything listed is something I have built with or run in production rather than read about.

Leadership and organization

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Organizational design Managing managers Hiring and succession Coaching and mentoring Retention Performance management Squad and tribe models Globally distributed teams Executive and board communication Roadmap and prioritization by business value Cross-functional partnership Build versus buy Vendor evaluation and negotiation Agile and Scrum Waterfall Sprint cadence and demo rhythm

Architecture and modernization

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Domain-driven design Bounded contexts Strangler pattern Zero-downtime cutovers Legacy to cloud migration Monolith to microservices Platform consolidation Datacenter consolidation Multi-tenant SaaS Vendor to in-house ownership DevOps automation Performance profiling Load testing Architecture Decision Records

AI and agentic systems

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Agentic frameworks Multi-agent orchestration MCP A2A RAG and hybrid retrieval Vector and similarity search Semantic re-ranking Context engineering Agent memory Guardrails Human in the loop Reasoning Workflow orchestration LLM inference

Generative AI and models

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Amazon Bedrock OpenAI Anthropic Gemini Per-use-case model routing Teacher-student distillation Small language models Fine-tuning Supervised fine-tuning Amazon Nova Pro Amazon Nova Lite

MLOps and evaluation

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AWS SageMaker Model CI/CD Model registry Continuous training Evaluation and golden sets Drift monitoring A/B experimentation Production observability Cost and latency tuning Throughput optimization

Data and big data

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Snowflake Medallion architecture Databricks Spark Kafka Airflow dbt Unstructured.io Knowledge graphs on AWS Neptune Hadoop Near-real-time pipelines Offline data platforms Instrumentation frameworks Lineage and metadata catalogs

Cloud and infrastructure

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AWS Google Cloud Azure Multi-cloud Private cloud Physical datacenter hosting Docker Kubernetes Bedrock AgentCore Strands SageMaker Cognito Splunk SignalFx

Platform engineering

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Internal developer platforms Backstage Golden paths Reusable SDKs Event-driven microservices Distributed systems Distributed session management Traffic shaping and load shedding API strategy Kong MuleSoft GraphQL Kiro IDE Amazon Q

Identity, security and governance

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IAM OIDC OAuth 2.0 JWT and JWKS AWS Cognito Single sign-on RBAC Fine-grained access control Zero Trust OWASP AI governance and responsible AI Auditability Data governance GDPR and CCPA WCAG 2.2 AA accessibility

Languages, frameworks and data stores

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Java Spring and Spring Boot Python JavaScript TypeScript React Single-page apps Micro-frontends Node.js J2EE EJB JSF Struts GWT MySQL Oracle PostgreSQL Aurora DynamoDB MongoDB Redis Amazon S3 OpenSearch
Certified Solutions Architect
Cloud architecture at professional level
Google Cloud Generative AI Leader
Agentic and generative AI leadership
Software Architecture for Leaders
O'Reilly architecture leadership program
B.E. Computer Science
Bachelor of Engineering