AI Platform Engineer

About the role

P&C IT Services provides professional services to help our business units and corporate functions use technology to create, manage, and optimize information and business processes. The AI Platform Engineer is a hands-on engineering role building and operating the enterprise AI platform that powers our Software Developer, Data Scientist, and Knowledge Worker communities.

Responsibilities

• Build and maintain core platform services including the LLM gateway, model registry, RAG pipelines, vectorization services, and MCP server infrastructure.
• Implement AI Foundry-based capabilities and integrate them with existing enterprise platforms (API gateway, IAM, observability, ECM).
• Develop reusable Python and/or Java libraries, SDKs, and golden-path templates that let consumers onboard in under an hour.
• Own the automation that provisions access, onboards models, runs compliance checks, and emits telemetry, so platform scale is never gated by team size.
• RAG and Vectorization Design and operate retrieval pipelines including chunking, embedding, vector store management, re-ranking, and evaluation.
• Tune retrieval quality against real consumer workloads and publish evaluation harnesses that let consumers measure their own RAG implementations.
• Integrate vectorization services with the ECM system and other enterprise data sources under the governance controls defined by the platform.
• Build, host, and operate MCP servers that expose enterprise capabilities safely to LLM consumers.
• Implement the authentication, authorization, rate limiting, and audit patterns that make MCP usage enterprise-ready.
• Partner with consuming teams to define and publish the MCP contracts the platform supports.
• DevOps and Operations Treat the platform as a product: CI/CD pipelines, IaC, automated testing, progressive delivery, and full observability are table stakes.
• Own the on-call rotation for the services you build. Write runbooks, automate the toil, and drive incident postmortems to real fixes.

Requirements

• 5+ years of software engineering experience with a strong development background.
• Hands-on experience with AI Foundry (or equivalent enterprise AI platforms) including model deployment, evaluation, and lifecycle management.
• Practical experience building RAG systems end-to-end: embeddings, vector databases (e.g., pgvector, Pinecone, Weaviate, Azure AI Search), retrieval tuning, and evaluation.
• Working knowledge of MCP server implementation and the patterns for exposing tools and data to LLMs safely.
• Strong DevOps practice: Git-based workflows, CI/CD pipelines, containers, Kubernetes, IaC (Terraform or equivalent), and observability tooling.
• Familiarity with LLM APIs, prompt engineering, token economics, and the failure modes of production LLM systems.
• Security and governance instincts: you assume every endpoint will be attacked and every model call will be audited.
• Platform engineering mindset: you build self-service capabilities with golden paths, not bespoke solutions for each consumer.

Qualifications

Prefer familiarity with the P&C Insurance industry.

Skills

• Software engineering
• AI Foundry
• RAG systems
• MCP server implementation
• DevOps practices
• LLM APIs
• Security and governance
• Platform engineering

Benefits

• Medical, dental, and vision coverage
• Wellness plans
• Parental leave
• Adoption assistance
• Tuition reimbursement
• Paid Time Off
• Paid holidays
• 401(k) plan with company match
• Employee stock purchase plan
• Commuter benefits

Pay

Compensation varies by role, level, and location and is influenced by skills, experience, and business needs. Your recruiter will provide details about benefits and specific compensation ranges during the hiring process.

Schedule

The AI Platform Engineer is expected to be on-site a minimum of two days a week if local to Cincinnati, with the potential to work three days remotely. Core in-office days are Tuesday and Thursday but will be determined by business needs.