Lead AI Engineer

Lead AI Engineer

This role seeks an established AI engineering subject-matter expert who applies deep domain and technical expertise to drive critical business outcomes. In this role, you will lead the design and deployment of complex, production-grade agentic systems—particularly multi-agent, multi-tool solutions that automate and enhance how the Services business operates. You will be responsible to build intelligent agents capable of reasoning, planning, and safely invoking tools; managing memory; and continuously improving through systematic evaluation and feedback.

About D&PE AI Solutions Team:

The Data & Productivity Engineering (D&PE) organization builds the data infrastructure, automation, and AI solutions that enable data-driven decision-making and scalable, efficient business processes across the Services division. Within D&PE, the AI Solutions team focuses specifically on improving productivity and employee experience by combining modern AI capabilities with existing and emerging data assets and platforms.

Key Responsibilities:

• Design, develop, and operate high-impact AI solutions that address complex business problems while improving productivity, efficiency, employee experience, and cost outcomes across the Services organization.
• Deeply understand requestor needs, impacted personas, underlying business processes, and jobs-to-be-done to recommend the most effective solution approach. Evaluate whether a given request is best addressed through agentic AI, process redesign, tactical automation, or improved documentation and governance.
• Define and enforce safe, scalable tool-use patterns for agentic systems, including structured outputs, robust error handling, permissioning and auditability, guardrails, and appropriate human-in-the-loop (HITL) approval workflows for sensitive actions.
• Own production observability and operational readiness for agentic solutions, including trace capture, cost and token telemetry, latency and reliability monitoring, and incident response for agent failures.
• Drive continuous improvement in system effectiveness, safety, and efficiency by defining clear success metrics such as task success rate, human intervention rate, policy violations, cost per task, and latency, and expanding evaluation coverage over time.

All About You:

• Agentic System Architecture: Hands-on experience designing multi-agent systems, goal decomposition and planning, tool and function calling, context engineering, harness design, memory and retrieval patterns, evaluations, etc.
• AI Platforms and Tooling: Practical experience with platforms such as Copilot Studio, Azure AI Foundry, Salesforce Agentforce, and Microsoft Power Platform.
• Production Engineering: Strong background in scalable deployment architectures, high-availability runtime design, failure handling, and overall operational excellence.
• Cross-Functional Leadership: Proven ability to collaborate with platform, security, governance, and business stakeholders; clearly communicate trade-offs; and drive adoption of shared standards and best practices.
• Communication and Stakeholder Management: Excellent written and verbal communication skills, with the ability to translate complex technical concepts into clear, actionable guidance for diverse audiences.