IT AI Senior Specialist

Eaton’s Corporate Sector division is currently seeking a IT AI Senior Specialist.  This position can sit out of any of our US Eaton locations on a hybrid schedule. The expected annual salary range for this role is $130000 - $190000 a year. This position is also eligible for a variable incentive program. Please note the salary information shown above is a general guideline only. Salaries are based upon candidate skills, experience, and qualifications, as well as market and business considerations.  What you’ll do: 
 Job Summary:   This is a hands-on senior individual contributor who leads the technical direction of the AI-Native Software Engineering pod inside Eaton's Data & AI Governance Office. The role designs, builds, and runs the platforms behind Eaton's AI Governance program, including the AI Control Tower, AgentOps, the AI Funnel, and AI FinOps tooling. The Pod Lead writes production code, sets engineering standards, and mentors a pod of three engineers, partnering with AI Architects, Solution Architecture, Cyber, Legal, Privacy, and Responsible AI & Oversight to turn policy into working software.   Key outcomes: • AI Control Tower MVP live in production, covering runtime signals, agent inventory, and unified audit log across Copilot Studio, AI Builder, and Power Automate. • AgentOps observability in production for the priority agent set, with tracing, evaluation scoring, and drift and hallucination monitoring wired into incident response. • AI FinOps dashboard reporting token, credit, and vendor-license spend by use case, with attribution back to owners. • Policy-as-Code framework live for the top 5 AI policies, with automated evidence collection into the AI Funnel intake. • Post-approval lifecycle monitoring stood up, closing Eaton's #1 AI maturity gap with per-use-case telemetry and named owners. • Pod operating on a healthy CI/CD, IaC, and SLO discipline, with published engineering standards adopted across both build pods. • Vendor and embedded AI telemetry ingested from ServiceNow, MuleSoft, Agentforce, and GitHub Copilot into the Control Tower for coverage reporting.   Job Responsibilities: • Set the technical direction, design standards, and engineering practices for the pod as a hands-on IC, contributing production code every sprint. • Design, build, and run the AI Control Tower, AgentOps, AI Funnel, AI FinOps, and Policy-as-Code capabilities that power Eaton's AI Governance program. [AIDG Capab...Org Model | PowerPoint] • Engineer observability, monitoring, compliance, and alerting across Eaton's AI estate, including post-approval lifecycle monitoring. [eaton-my.s...epoint.com] • Build with AI-native patterns first: LLM apps, agents, RAG, and automated workflows as core components, not bolt-ons. • Translate AI policy and risk requirements into working software, partnering with Cyber, Legal, Privacy, and Responsible AI & Oversight. [eaton-my.s...epoint.com] • Own architecture and design for complex, integrated systems: interfaces, data structures, storage, integrations, and deployment. • Set and defend non-functional requirements: scalability, performance, reliability, security, and cost. • Manage the LLM lifecycle for pod-built solutions: prompt versioning, eval design, accuracy scoring, and drift and hallucination monitoring. [eaton-my.s...epoint.com] • Optimize token, credit, and cloud consumption; design model routing, caching, and cost attribution into every use case. [eaton-my.s...epoint.com] • Ingest telemetry from embedded and vendor AI (ServiceNow, MuleSoft, Agentforce, GitHub Copilot) into the AI Asset Catalog and Control Tower. [eaton-my.s...epoint.com] • Provide dotted-line technical leadership to three engineers: design reviews, code reviews, coaching, and technical growth planning. • Run a continuous delivery pipeline with secure SDLC, IaC, and automated testing baked in from day one. Qualifications: 
 Basic (required) Qualifications: