Agentic Engineering Lead

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 Lang. Graph 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 Lang. Smith 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 What We Are Not Looking For
• Someone who lists LLMs on a resume but has only called the API in a Jupyter notebook
• AI enthusiasts whose hands-on experience is less than a year old
• People who explain everything in terms of frameworks they have never deployed
• Consultants who can only narrate what others have built Key Responsibilities Delivery & Architecture
• Own end-to-end delivery of AI-native programs - from architecture through production deployment
• Design and build multi-agent orchestration systems using Lang. Chain, Lang. Graph, 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 Lang. Chain, Lang. Graph, CrewAI - not just conceptual Agentic Coding Tools Claude Code CLI, Cursor, OpenAI Codex, Copilot RAG & Vector Stores Chroma, Weaviate, Pinecone - knows where RAG breaks LLM APIs & SDKs Anthropic, OpenAI, Gemini - prompt design, tool use Python / TypeScript Primary languages for agent + backend development Lang. Smith / Observability Tracing, evaluation, debugging agent runs Cloud Platforms Azure, AWS, GCP (at least one) - deployment, infra, managed services API & System Integration REST, gRPC, Kafka - enterprise integration patterns MCP / Shared Context Model Context Protocol, CLAUDE.md, Beads Agent Evaluation Testing non-deterministic outputs, guardrails, evals CI/CD & DevOps Git, containers, pipelines - agents need to ship Client Communication Can present architecture to a CXO without jargon How We Will Evaluate You Not a theory round. Expect to walk through something you have actually built - architecture decisions, what broke in production, what you would do differently. If you cannot do that with specifics, this role is not the right fit. Evaluation stages:
• Stage 1
• Technical screen: Walk us through a live agent system you built
• Stage 2
• Architecture discussion: Given a business problem, design an agent solution on the spot
• Stage 3
• Stakeholder simulation: Present your approach to a non-technical executive audience