Description

Key Responsibilities

• 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 APIs, ERPs, CRMs, and data platforms
• Define agent topology: tool routing, memory strategy, state machines, and fallback handling
• Translate business problems into agent architectures for global CXO-level stakeholders
• Run discovery workshops, solution reviews, and delivery cadences with client teams
• Mentor junior AI engineers and raise engineering quality across the delivery team
• Evaluate new models, frameworks, and tooling continuously

Required Skills

• Agent Orchestration: LangChain, LangGraph, CrewAI (production-deployed, not conceptual)
• Agentic Coding Tools: Claude Code CLI, Cursor, OpenAI Codex, GitHub Copilot
• RAG & Vector Stores: Chroma, Weaviate, Pinecone
• LLM APIs: Anthropic, OpenAI, Gemini — prompt design and tool use
• Languages: Python, TypeScript
• Observability: LangSmith — tracing, evaluation, debugging agent runs
• Cloud Platforms: Azure, AWS, or GCP (at least one — deployment, infra, managed services)
• Integration: REST, gRPC, Kafka — enterprise integration patterns
• Shared Context: Model Context Protocol (MCP), CLAUDE.md
• CI/CD & DevOps: Git, containers, pipelines

Preferred Skills

• Experience with Claude Code CLI in team environments (shared context, multi-session flows)
• LangSmith for agent tracing and evaluation pipelines at scale
• Shipped projects using MCP or similar shared-context tooling
• QA/testing mindset for non-deterministic agent outputs
• Background in IT services or consulting
• Experience with SLMs, fine-tuning, or edge/on-device agent deployment

Key Skills

Education

Bachelor's degree