About the Role :

This is not a slide-making or prompt-engineering role. We are looking for someone who has built multi-agent AI systems that run in production - not demos, not pilots that died after a sprint. You will anchor AI delivery programs end-to-end, work directly with global clients, and stay sharp on a field that changes every few weeks.

You will report into and replicate the function of a senior AI delivery leader - which means you need both the depth to architect solutions and the presence to walk a CXO through what you built and why it works.

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 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