Job Summary
The AI/ML Engineer Lead is responsible for developing, deploying, and supporting enterprise-grade agentic AI solutions and integrations. This role involves building production-ready AI agents, developing Model Context Protocol (MCP) servers and connectors, integrating shared AI platform capabilities, and translating business workflows into agent skills. The engineer will work independently across the solution lifecycle, collaborate with subject matter experts and operational teams, and contribute reusable engineering practices and platform improvements.
Key Responsibilities
• Build and deploy AI agents in close collaboration with subject matter experts and operational teams.
• Develop and deploy MCP servers and connectors, progressing solutions from pre-production through design review into production.
• Configure skills, integrations, and evaluations using AI platform capabilities, including the LLM gateway, shared Retrieval-Augmented Generation (RAG) services, and MCP toolchain.
• Conduct workshops with teams, provide guidance on using Claude Code, and translate business workflows into agent skills.
• Transition mature systems to platform and operations teams when they are ready for ongoing support.
• Share engineering patterns, anti-patterns, and platform gaps with the Center of Excellence to improve delivery practices and engineering efficiency.
• Design, develop, deploy, and support production AI agents and integrations independently.
• Use AI-assisted development tools and workflows to improve engineering productivity while maintaining accountability for solution quality and production outcomes.
• Coordinate and run multiple AI agents in parallel as part of daily engineering workflows.
• Evaluate system failure modes and determine when solutions are ready for release, require further hardening, or should be handed off.
Required Qualifications
• Experience developing and hosting enterprise agentic solutions using Claude Agent SDK, Model Context Protocol (MCP), or an equivalent technology stack.
• Production coding experience in at least one of Python, Node.js, or .NET, with the ability to work across the other technologies.
• Experience working with diverse data stores, including relational, NoSQL, object/blob, vector, and document databases.
• Experience independently managing the end-to-end solution lifecycle, including design, development, deployment, production support, and handoff.
• Strong written and verbal communication skills, including the ability to collaborate with and present technical concepts to non-engineering stakeholders.
• Pragmatic judgment in determining when to release solutions, when to improve production readiness, and when to transition ownership.
• Strong systems-thinking skills with a focus on failure modes, reliability, and accountability for production outcomes.
• Ability to work effectively with AI-assisted development tools and manage multiple agents in parallel.
