About the Role
We are looking for a Senior Product Manager for our AI Platform to drive the execution and delivery of Aurigo's proprietary AI foundation model, agent framework, and the AI platform layer that powers our products. This is a hands-on product role that operates at the intersection of AI engineering, enterprise software, and capital program workflows. You will partner closely with engineering, data science, and design teams to define, build, and ship AI capabilities that are safe, measurable, and impactful in enterprise environments. Unlike the Director role which is focused on strategy, vision, and stakeholder leadership, this role is about deep execution. You will own specific product areas end to end, write detailed requirements, drive sprint-level delivery, and ensure that AI products meet well-defined quality and safety standards before reaching customers. You will also engage with customers and internal product teams to ground your decisions in real-world use cases.
Roles and Responsibilities
- Own and execute the product roadmap for assigned areas of the AI platform, including the ingestion and context layer, orchestration layer, agent framework components, and the Copilot experience across all product lines.
- Write detailed product requirements, user stories, and acceptance criteria for AI features, and drive sprint planning, backlog grooming, and delivery tracking in close partnership with engineering and machine learning teams.
- Define and maintain the evaluation framework for assigned AI features including offline evals, benchmark metrics, regression tests, and production monitoring. No agent or model capability ships without defined success criteria.
- Own the responsible AI execution process at the feature level, including guardrail testing, safety checklists, bias review, and auditability verification before any AI capability reaches customers.
- Serve as the internal AI platform expert for Senior Product Managers across all product lines, providing guidance on how to correctly integrate, specify, and evaluate AI capabilities within their respective workflows.
- Contribute to the model management and MCP server roadmap by gathering data on provider performance, cost, and quality, and by identifying integration opportunities and validating tool specifications.
- Engage with enterprise customers to gather feedback on AI feature performance, understand adoption patterns, and translate insights into roadmap decisions.
- Monitor the competitive landscape for relevant AI product developments, agent frameworks, and enterprise AI tooling, and bring insights into prioritization discussions.
