Production AI Engineering
Agentic AI · Model Context Protocol (MCP) · RAG · LLM Engineering

I architect production AI systems — the multi-tenant authorization, evaluation harnesses, guardrails, observability, and operational discipline that take RAG, agentic AI, and Model Context Protocol (MCP) from impressive demos to dependable infrastructure.

Sixteen years building data-intensive systems, with the last several focused on shipping retrieval-augmented generation agents, multi-agent orchestrations, secure tool-server (MCP) deployments, and the data-readiness methodologies that decide whether enterprise AI actually works at scale.

Agentic AI · Agentic Orchestration · Model Context Protocol (MCP)
RAG · Knowledge RAG / GraphRAG · Hybrid Retrieval · Vector Databases
LLM Engineering · LLM Evaluation · LLM Observability · LLM Guardrails
AI Platform Engineering · AI Governance · AI FinOps
Distributed Systems · Apache Spark · Databricks · AWS · Kubernetes
LangGraph · LangChain · LangSmith · Datadog LLM Observability

mcp-enterprise-patterns — Reference patterns for shipping a Model Context Protocol server into production: OAuth, JWT validation, multi-tenant authorization (Redis / DynamoDB), OpenTelemetry tracing, Datadog observability.

rag-eval-cookbook — Practitioner recipes for evaluating production RAG: faithfulness, context precision, behavioural regression, drift detection. RAGAS, DeepEval, and LangSmith integrations included.

ai-ready-data-toolkit — Pre-LLM data-readiness utilities: labelling helpers, embedding-quality evaluation, similarity-scoped retrieval, document-level deduplication before chunking.

agentic-orchestration-patterns — LangGraph reference patterns for multi-agent workflows: supervisor patterns, hand-off contracts, cost-aware routing, and failure-mode design.

I write practitioner essays on production AI engineering patterns. Recent on Medium:

• Why Your RAG Demo Doesn't Survive Production — the data-readiness gap that decides whether your RAG ships
• More long-form pieces at anwarkhan.org and on Medium

Available for keynote, breakout, panel, podcast, technical advisory, judging, and peer review on production AI/ML systems.

Recent and recurring topics:

• Lessons From Shipping a Production MCP Server
• Agentic Orchestration Patterns That Don't Burn Tokens
• GraphRAG vs Vector RAG: When the Knowledge Graph Pays Off
• LLM Observability for Production
• Harness Engineering for Production LLMs
• LLM Guardrails for Enterprise Audit

Full talk library: sessionize.com/anwar-khan

• Federated Learning for Secure Blockchain-Based Identity Verification in Decentralized Systems (2025)
• Design and Implementation of SVM-Based Genetic Algorithm for Forensic Investigation of Cloud Data
• Novel Approach for Forensics Investigation in Cloud Computing Environments (2016)

Full record: Google Scholar · ORCID

AWS Certified Solutions Architect — Professional · AWS Certified DevOps Engineer — Professional

For speaking, advisory, peer review, or collaboration: hello@anwarkhan.org

If you're putting RAG, agentic AI, or MCP through enterprise audit, evaluation, or scale — let's talk.