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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. Ā 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, Ā 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.
Great Americanās culture is built on connection, shared learning, and strong relationships. To support this, employees in this role are 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 ināoffice days are Tuesday and Thursday but will be determined by business needs.Ā
As the insurance industry undergoes digital transformation, the AI Innovation Lab serves as Great Americanās proving ground for emerging AI capabilities. Team members evaluate, prototype, andĀ validateĀ AI technologies againstĀ real businessĀ needs,Ā determiningĀ whatāsĀ ready for enterprise adoption and whatĀ isnāt. This is appliedĀ researchĀ with a purpose: every initiative ties directly to business requests, and successfulĀ proofs-of-concept are handed off to IT delivery teams for production implementation.Ā Ā
What Makes This Role UniqueĀ
ThisĀ isnātĀ a traditional research position, and itĀ isnātĀ a traditional development role.Ā ItāsĀ something in betweenānow with senior product ownership and change leadership:Ā
Vision-to-value ownership: You create and evolve the Labās product vision andĀ roadmapĀ so work stays tightly aligned to enterprise priorities and measurable outcomes.Ā Ā
Rapid experimentation:Ā YouāllĀ go deep onĀ a technology, guide the team to build working prototypes,Ā determineĀ fit-for-purpose, and move to the next challenge.Ā Ā
Business-driven focus: Every project originates fromĀ a real businessĀ askāsupporting underwriters, actuaries, claims professionals, and analysts across the enterprise.Ā Ā
Fail-fast culture: A well-documented āno, and hereās whyā is as valuable as a successful proof-of-concept.Ā Ā
Partnership model to production: You work with Enterprise Architecture and IT deliveryĀ teamsĀ so innovations can be operationalizedānot just demoed.Ā Ā
Human-in-the-loop philosophy: Ethical, transparent, explainable AI is foundational in insurance; you ensure designs reflect that from day one.Ā Ā
Key ResponsibilitiesĀ
1) Vision Creation & Product StrategyĀ
Define and communicate the AI Innovation Lab product vision, outcomes, and success metrics;Ā maintainĀ a roadmap that balances innovation with enterprise readiness.Ā Ā
Create decision frameworks forĀ adoptĀ /Ā adaptĀ / defer /Ā rejectĀ outcomes so the Labās learning directly informs enterprise AI strategy.Ā Ā
Own prioritization of initiatives across multiple business requests based on value, feasibility, risk, and operational constraints.Ā Ā
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2) Customer Engagement (Business Stakeholders) & Executive CommunicationĀ
Serve as the primary Lab-facing leader for business stakeholders and executives: intake, discovery, expectation-setting, and ongoing engagement.Ā Ā
Translate ambiguous business asks into clear problem statements, hypotheses, and acceptance criteria for research and prototypes.Ā Ā
Deliver clear, credible readoutsāable to explain tradeoffs, risks, and readiness to both technical and non-technical audiences.Ā Ā
3) Product Design & Research PlanningĀ
Drive product discovery: user journeys, workflow design, guardrails, human-in-the-loop controls, and measurable definitions of value.Ā Ā
Partner with technical team members to ensure prototypes align with enterprise constraints and API-first integration principles.Ā Ā
Ensure evaluation plans exist before building (quality measures, go/no-go criteria, and what āgoodā looks like).Ā Ā
4) Research Delivery & Transition to ProductionĀ
Oversee rapid prototypes andĀ proofs-of-conceptĀ fromĀ concept through stakeholder validation; ensure learnings are documented (wins and failures).Ā Ā
Coordinate with Enterprise Architecture and IT delivery teams to shape handoffs that can succeed in production (security, operations, integration, support model).Ā Ā
Ensure the Lab produces ādecision-gradeā outputs: feasibility, limitations, risk, and a recommended path forward.Ā Ā
5) Full-Stack AI Lifecycle Ownership & OptimizationĀ
Demonstrated understanding of the full AI product lifecycle: problem framing ā data readiness ā model/approach selection (ML vs GenAI) ā prototyping ā evaluation ā governance/security ā production transition ā monitoring and continuous improvement.Ā Ā
Drive optimization across performance, cost, and reliability: latency/throughput, retrieval quality (RAG), prompt/agent instruction tuning, and regressionĀ control asĀ systems evolve.Ā Ā
ChampionĀ MLOps/LLMOpsĀ practices: reproducibility, versioning (models/prompts), CI/CD patterns, monitoring, and controlled rollout strategies.Ā Ā
6) AI Agents & Customer-Facing AI ApplicationsĀ
Demonstrated experience creating AI agents (single and multi-agent) that use tools/APIs to execute workflows with guardrails and human oversightĀ appropriate forĀ insurance.Ā Ā
Experience building customer-facing AI applications (internal customers such as underwriting, claims, actuarial, and analytics teams), including conversational UX patterns, RAG grounding, structured outputs, and feedback loops that build user trust.Ā Ā
Define and drive production readiness for agent solutions (failure modes/fallbacks, monitoring, operational handoff expectations) in partnership with Enterprise Architecture and delivery teams.Ā Ā
7)Ā Team Management & People LeadershipĀ
The Product Owner also leads the Data Science team, ensuring clear goals, effective prioritization, andĀ highqualityĀ delivery. TheyĀ are responsible forĀ performance management, talent development, and supportingĀ HRrelatedĀ activities that foster a healthy, collaborative team culture. This includes guiding career growth,Ā facilitatingĀ feedback cycles, and aligning team capabilities with evolving business needs.Ā
8)Ā Change Leadership & CultureĀ
Act as a visible change leaderāguiding adoption of AI-enabled workflows, building trust through transparency, and ensuring responsible use.Ā Ā
Mentor teamĀ members andĀ contribute to a culture of continuous learning and high-quality delivery.Ā Ā
Required QualificationsĀ
Proven senior leadership in product ownership/product management/innovation leadership delivering outcomes in ambiguous environments (especially where technology feasibility must be proven).Ā Ā
Exceptional written and verbal communication skillsāable to align executives, business stakeholders, and technical teams; strong storytelling with evidence.Ā Ā
Strong understanding of enterprise integration principles, including API-first thinking and how AI capabilities transition into production systems.Ā Ā
Strong understanding of AI/ML and GenAI solution patterns sufficient to lead discovery and evaluate approaches objectively (including ML evaluation fundamentals and LLM/RAG patterns).Ā Ā
Demonstrated experience creating AI agents and customer-facing AI applications withĀ appropriate guardrailsĀ and human-in-the-loop controls.Ā Ā
Demonstrated understanding ofĀ MLOps/LLMOps, evaluation rigor, monitoring, and optimization across performance, cost, and reliability.Ā Ā
Preferred QualificationsĀ
Experience in insurance, financial services, or other regulated industries.Ā Ā
Hands-on familiarity with agentic AI frameworks and orchestration patterns such asĀ LangChainĀ /Ā LangGraph,Ā CrewAI, or similar.Ā Ā
Familiarity with enterprise AI interoperability patterns and standards such as Model Context Protocol (MCP), tool registries, and A2A (agent-to-agent) coordination concepts for enterprise workflows.Ā Ā
Experience with Microsoft Azure cloud services.Ā Ā
Background working with actuarial, underwriting, or claims processes and/or experience transitioning prototypes to production teams.Ā Ā
Business Unit:
Property & Casualty IT ServicesBenefits:
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.
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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.
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*Excludes seasonal employees and interns.
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