Delivery & Architecture
* Own end-to-end delivery of AI-native programs – from architecture through production deployment
* Design and build multi-agent orchestration systems using LangChain, LangGraph, CrewAI, or equivalent
* Integrate agent systems with enterprise surfaces: APIs, ERPs, CRMs, data platforms – not toy datasets
* Define agent topology: tool routing, memory strategy, state machines, fallback handling
Agentic Coding & Development
* Run agentic coding workflows using Claude Code, Cursor, OpenAI Codex, or equivalent CLI tools
* Lead projects where AI writes significant portions of the codebase – and you guide, review, and ship it
* Work with CLAUDE.md, shared context frameworks, and multi-session agent setups for team use
* Debug non-deterministic agent outputs systematically – not by gut feel
Client & Stakeholder Engagement
* Translate business problems into agent architectures for global CXO-level stakeholders
* Run discovery workshops, solution reviews, and delivery cadences with client teams
* Prepare and present technical proposals, POC plans, and roadmaps – own the story end-to-end
Team & Practice
* Mentor junior AI engineers; raise AI engineering quality across the delivery team
* Stay current: evaluate new models, frameworks, and tooling before the hype catches up
* Contribute to internal knowledge bases, reusable frameworks, and accelerators
Skills
* Agent Orchestration
o LangChain, LangGraph, CrewAI – not just conceptual
* Agentic Coding Tools
o Claude Code CLI, Cursor, OpenAI Codex, Copilot
* RAG & Vector Stores
o Chroma, Weaviate, Pinecone – knows where RAG breaks
* LLM APIs & SDKs
o Anthropic, OpenAI, Gemini – prompt design, tool use
* Python / TypeScript
o Primary languages for agent + backend development
* LangSmith / Observability
o Tracing, evaluation, debugging agent runs
* Cloud Platforms
o Azure, AWS, GCP – deployment, infra, managed services
* API & System Integration
o REST, gRPC, Kafka – enterprise integration patterns
* MCP / Shared Context
o Model Context Protocol, CLAUDE.md, Beads
* Agent Evaluation
o Testing non-deterministic outputs, guardrails, evals
* CI/CD & DevOps
o Git, containers, pipelines – agents need to ship
* Client Communication
o Can present architecture to a CXO without jargon
What You Must Have Actually Done
Not just what you know. What you have shipped.
* Deployed 2–3 agent-based systems in production – stateful, multi-step, real users
* Used LangGraph for multi-agent orchestration with memory, tool routing, and state management
* Built projects where AI (Claude Code, Codex, Cursor) wrote significant portions of the code
* Implemented RAG pipelines end-to-end – chunking, embedding, retrieval, re-ranking, evaluation
* Integrated agents with real enterprise APIs – not just OpenAI playground or sample data
* Debugged a production agent failure – and fixed it without blaming the model
* Can articulate when NOT to use agents – that is how we know you have built things
Bonus - Real Differentiators
* Experience with Claude Code CLI in team environments (CLAUDE.md, shared context, multi-session flows)
* Familiarity with LangSmith for agent tracing, evaluation pipelines, and debugging at scale
* Has shipped something using MCP (Model Context Protocol) or similar shared-context tooling
* QA/testing mindset for agents – systematic evaluation of non-deterministic outputs
* Background in IT services or consulting – managing client expectations while building
* Experience with SLMs, fine-tuning, or on-device/edge agent deployment
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