Lead AI Engineer – Enterprise, Data & AI

Job description

Job responsibilities

• Design and deploy production-grade LLM applications and intelligent agents capable of complex reasoning, secure tool usage and autonomous multi-step workflows.
• Architect enterprise data/tool integrations using MCP servers, establishing standardized, reusable connectors across Procurement, Supply Chain, Legal, Finance, HR and Manufacturing (MES).
• Enforce security guardrails via AI gateways - authentication, rate-limiting, logging and policy compliance for all model/agent traffic.
• Implement identity inheritance via SSO, ensuring agents act strictly within the requesting user's permissions & privileges (no privilege escalation, no standing overreach).
• Work with the Information Security team on access control (RBAC/ABAC) for agentic systems and establish observability standards for agent behavior and data access.
• Partner with cross-functional teams to build secure, code-driven AI automation.

Job 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).
• Experience building AI solutions for corporate functions like Finance, Legal (e.g. contract analysis), HR (e.g. policy retrieval), Supply Chain (e.g.
• Familiarity with AI platform vendor evaluations (Bedrock, Vertex, Cortex, etc.)