Expertise

AI & Agentic Systems

Architecture for production AI: agent runtimes, retrieval, model routing, tools, memory, gateways, evaluation, and the enterprise systems they connect to.

• LLM application and agent architecture
• Multi-agent orchestration and tool-calling gateways
• Retrieval-augmented generation and retrieval quality
• Embeddings, vector search and document ingestion pipelines
• Structured output and function calling
• MCP and A2A as enterprise integration surfaces
• Guardrails, evaluation and human-in-the-loop review
• Model routing and multi-model architectures

• Python
• Node.js
• AWS
• Azure
• PostgreSQL
• Redis

AI-Native Software Engineering

Redesigning the software delivery lifecycle around coding agents, specifications, automated verification, and human judgment.

• Specification-driven development with AI agents
• AI-assisted architecture and documentation generation
• Legacy source and dependency analysis at scale
• Test generation with human validation gates
• AI-assisted code review and its limits
• Governance for AI-assisted delivery

• Claude Code
• MCP
• Git
• JavaScript
• Python

Cloud & Platform Engineering

Cloud and infrastructure architecture across AWS, OCI, and Azure: Kubernetes, gateways, networking, observability, and infrastructure as code.

• AWS and Azure platform architecture
• Kubernetes and container orchestration
• Serverless and event-driven infrastructure
• High availability, networking and caching strategy
• CI/CD pipelines and deployment strategy
• Observability and operational readiness

• AWS
• Azure
• Oracle Cloud
• Kubernetes
• Docker
• Redis

Engineering Leadership

Leading complex technical initiatives, setting architectural direction, developing engineers, and turning experimentation into repeatable engineering practice.

• Technical strategy and architecture governance
• Leading teams through complex, ambiguous delivery
• Mentoring engineers and architects
• Driving AI adoption without abandoning engineering discipline
• Technical decision-making and trade-off communication
• Engineering process transformation

Security

Security designed into the architecture from the start: identity, network boundaries, credentials, tenant isolation, secure delivery, and AI guardrails.

• Cloud and application security architecture
• Identity and access management
• Secure SDLC practice
• Credential isolation and secure tool execution for AI systems
• Network and perimeter architecture
• Security governance and review

• AWS
• Azure
• Check Point CloudGuard
• Kubernetes

Software Architecture

Designing distributed, integration-heavy enterprise systems that evolve without losing reliability, clarity, or operational control.

• Distributed and service architecture
• API and integration design
• Event-driven architecture
• Scalability and resilience patterns
• Legacy integration and incremental modernization
• Architecture review and technical decision records

• Node.js
• Java
• Python
• Go
• React
• PostgreSQL

Data

The data layer behind enterprise applications and AI systems: relational modeling, caching, retrieval, vector search, ingestion, and performance.

• Relational data modeling and query performance
• Document and key-value data design
• Vector search and embedding storage
• Document ingestion and RAG pipelines
• Caching strategy

• PostgreSQL
• Oracle
• SQL Server
• MongoDB
• Redis
• MySQL