Director, AI and Agentic Engineering

Responsibilities

• Define and own the enterprise AI architecture, spanning LLMs, SLMs, fine-tuned models, and retrieval-augmented systems
• Establish model selection frameworks
• Design and govern AI infrastructure: vector databases, embedding pipelines, model registries, and inference optimization
• Lead the adoption and governance of Model Context Protocols (MCPs)
• Architect multi‑agent systems capable of reasoning, planning, and executing across complex business processes
• Design agent orchestration patterns
• Lead end‑to‑end business process automation using AI
• Collaborate with process owners to identify and prioritize automation opportunities with measurable ROI
• Develop and maintain the enterprise AI roadmap
• Build and enforce AI governance frameworks
• Act as the internal AI thought leader
• Recruit, develop, and lead a high‑performing AI team
• Build a center‑of‑excellence model that distributes AI capability and fluency across business units

• 10+ years in software engineering, data, or applied AI with at least 3 years in senior AI/ML leadership role
• Deep hands‑on expertise with large language models (GPT-4 class, Claude, Llama, Mistral) and small language models in production
• Proven track record architecting and deploying agentic AI systems using frameworks such as Lang Graph, Auto Gen, CrewAI, or equivalent
• Strong command of Model Context Protocols (MCPs) and tool‑use patterns for connecting agents to enterprise systems
• Experience leading end‑to‑end AI‑powered business process automation — not just prototypes, but production‑grade systems with SLAs
• Proficiency in Python and familiarity with cloud AI ecosystems (AWS Bedrock, Azure OpenAI, GCP Vertex AI)
• Demonstrated ability to translate ambiguous business problems into structured, solvable AI architectures
• Must have used Claude Code, Codex or Github Copilot in the prior roles