Shape enterprise agentic AI strategy and architecture, advise C-suite clients, and lead complex programmes from pursuit through production delivery while establishing safe, reusable engineering practices and growing team capability.
Lead AI Engineer – Enterprise, Data & AI
📜 Description
- Design and deploy production-grade LLM applications and intelligent agents for complex reasoning, secure tool use, and multi-step workflows.
- Build reusable MCP-based integrations with Procurement, Supply Chain, Legal, Finance, HR, and Manufacturing systems.
- Apply AI gateway controls for authentication, rate limiting, logging, and policy compliance.
- Implement SSO identity inheritance so agents operate within the requesting user's permissions.
- Partner with Information Security on RBAC/ABAC access controls and agent observability standards.
- Collaborate across teams to deliver secure, code-driven AI automation.
🛠️ Requirements
- 10+ years in Data/Software Engineering, with 2+ years deploying GenAI/LLMs in production.
- Deep Python proficiency; experience with LangChain, LlamaIndex or provider-native orchestration (e.g., Claude Agent SDK, OpenAI Assistants/Agents SDK or hand-rolled).
- Hands-on experience building/integrating MCP servers or comparable connector frameworks.
- Experienced in AI gateway solutions (e.g. Cloudflare AI Gateway) for governing agent traffic.
- Working knowledge of SSO/identity federation (SAML, OIDC, OAuth 2.0) and propagating identity through agentic tool calls.
- Experience with cloud AI services (AWS Bedrock, Google Vertex AI) and vector databases (MongoDB, Pinecone, Weaviate, Milvus, OpenSearch).
Full job description
In this role, you will:
Qualifications:
Bonus Qualifications:
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