AI Implementation Lead
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About the Role
At IEM, we’re not just building innovative electrical distribution systems, we’re shaping the future. IEM is dedicated to delivering world-class solutions for complex power needs. After 75 years, we continue to push the boundaries of what’s possible. Whether you’re an experienced professional or just starting out, you’ll have the opportunity to contribute, grow, and make a lasting impact on industries that power the world’s most dynamic markets.
Position Summary
The AI Implementation Lead is the Data Team's hands-on builder, deploying AI solutions where Data Team work meets the business. The ideas are coming faster than the implementation; this role exists to close that gap. The work spans agents, plug-ins, applications, integrations, and whatever form the use case calls for. You will scale IEM's existing AI-native infrastructure (Claude Code in daily use, multiple local MCP servers wired to production data systems, an internal multi-agent portfolio across analytics and operations, and an established AI-assisted development culture) from a director-led prototype into a Data Team production platform. This role works in coordination with IEM's Enterprise AI team, which sets enterprise AI strategy and policy; the AI Implementation Lead applies that framework to the solutions you build rather than authoring it. This is the first dedicated AI engineer on the Data Team, offered with track flexibility as either a principal individual contributor or a hands-on people leader managing 2 to 4 engineers as the function scales.
Ideal Candidate Profile
You have 5+ years of software engineering experience with hands-on AI and agentic system development. You have built agents, plug-ins, or AI applications that real organizations have used, not coursework or POCs. You think first about the use case and the user, then about the system, then about the model. You write production code yourself and pride yourself on building solutions that actually get adopted. You partner naturally with non-technical stakeholders, translating fuzzy AI ideas into deployed solutions and surfacing the questions behind the questions. You are comfortable working with modern agent tooling such as Claude Code, MCP, LangGraph, Mastra, or Pydantic AI, and you treat AI-assisted development as a daily multiplier for engineering, governance, documentation, and adoption work. You have a working knowledge of AI governance and security including prompt injection mitigation, data leakage prevention, and model risk. You are excited about defining a new function inside a Data Team that already has the foundation in place.
Key Responsibilities
- AI Solution Deployment: Build agents, plug-ins, applications, and integrations as use cases emerge from the Data Team's work and the partners it supports
- Agent Development: Design and develop custom agents and agent harnesses, including MCP servers, orchestration logic, prompt engineering, and eval scaffolding. Agents are the centerpiece of the function.
- Vendor AI Extension: Build on top of Salesforce Einstein, Tableau Pulse-AI, ETQ-AI, Fellow.ai, and the data-platform AI capabilities IEM brings on next
- Solution Discovery: Run intake conversations with internal partners to surface high-value AI use cases, pressure-test feasibility against existing tooling, and prioritize the implementation roadmap
- AI Governance and Security: Build with data leakage prevention, prompt injection mitigation, and model risk as first-class concerns, in alignment with IEM's broader AI policy framework
- Adoption and Enablement: Train users, write documentation, and run enablement programs so the AI solutions you deliver get used by the people they were built for
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