AI Platform Engineer

Location: Cincinnati, OH (USA)

Remote Type: Hybrid

Time Type: Full time

Job Description

Be Here. Be Great. Working for a leader in the insurance industry means opportunity for you. Great American Insurance Group's member companies are subsidiaries of American Financial Group. We combine a "small company" culture where your ideas will be heard with "big company" expertise to help you succeed. With over 30 specialty and property and casualty operations, there are always opportunities here to learn and grow.

At Great American, we value and recognize the benefits derived when people with different backgrounds and experiences work together to achieve business results. Our goal is to create a workplace where all employees feel included, empowered, and enabled to perform at their best.

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.  IT Services can include a wide range of activities such as: software development, data management, Cloud services, IT security, network security, technical support, establishing and overseeing access rights, procuring and maintaining equipment or software, managing the infrastructure, and defining security procedures,  The overall goal of IT Services is to provide technology solutions that increase efficiency, reduce costs, and give our company a competitive advantage over our competitors.

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. You will design, implement, and run the platform services that make LLMs, RAG systems, and MCP servers safely consumable across the enterprise.

You will work inside a small, high-leverage platform team where code quality, automation, and operational excellence are the expectation, not the goal. You will report to the AI Platform Delivery Leader.

What You'll Own

Platform Engineering

• 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.

MCP and Agent Infrastructure

• 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 the runbooks, automate the toil, and drive incident postmortems to real fixes.

• Build safety, governance, and compliance controls into the pipeline so they are enforced by default, not added later.

What You Bring

• 5+ years of software engineering experience with a strong development background. You write production code, not just scripts.

• 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.

• Prefer familiarity with the P&C Insurance industry

How You'll Be Measured

• Reliability and performance of the platform services you own.

• Time-to-value for consumers onboarding to RAG, MCP, and LLM gateway capabilities.

• Automation coverage and reduction in manual operational work over time.

• Quality of retrieval and agent infrastructure as measured by consumer evaluation results.

• Code quality, test coverage, and operational maturity of the services you ship.

Business Unit:

Benefits:

We offer competitive benefits packages for full-time and part-time employees*. Full-time employees have access to medical, dental, and vision coverage, wellness plans, parental leave, adoption assistance, and tuition reimbursement. Full-time and eligible part-time employees also enjoy Paid Time Off and paid holidays, a 401(k) plan with company match, an employee stock purchase plan, and commuter benefits.

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. Learn more at http://www.gaig.com/careers.

*Excludes seasonal employees and interns.