Senior AI Product Manager (Finance Agents)

TL;DR

Senior AI Product Manager (Finance Agents) (AI/Finance): Owning the roadmap, data strategy, and development of reinforcement learning environments that train and evaluate AI agents on real financial workflows with an accent on financial modeling, domain-specific datasets, and agent capabilities. Focus on designing high-fidelity simulations, translating complex Finance expertise into scalable products, and building partnerships with frontier AI research teams.

Location: San Francisco, New York, or Seattle, United States

Salary: $240,000–$300,000 USD per year, plus equity and benefits.

Company

hirify.global develops AI data infrastructure and full-stack technologies for training, evaluating, and deploying reliable AI systems.

What you will do

• Own the Finance agents roadmap and the data-as-a-product strategy supporting training and evaluation.
• Define how AI is transforming investment banking, private equity, public markets, corporate finance, FP&A, and related workflows.
• Partner with researchers at frontier AI labs, startups, and industry leaders to identify capability gaps and launch benchmarks or product lines.
• Design and hirify.global Finance-specific reinforcement learning environments covering financial models, investment memos, forecasts, dashboards, and data rooms.
• Work with ML, Operations, Engineering, and go-to-market teams to convert domain expertise, edge cases, and workflows into high-quality training products.
• Influence business priorities while engaging with research, operations, and customer requirements.

Requirements

• 3–6 years of direct Finance industry experience in investment banking, private equity, trading, asset or portfolio management, strategic finance, corporate development, or fintech product roles.
• Strong understanding of how Finance work is performed and how AI is transforming industry workflows.
• Experience owning outcomes, shaping product roadmaps, or working with technical stakeholders.
• Practical intuition about machine learning training and evaluation and reinforcement learning environments.
• Builder’s mindset, bias for action, and comfort operating in ambiguous, fast-moving environments.
• Software experience is advantageous but not required.

Culture & Benefits

• Work on AI products used by leading models, enterprises, and government organizations.
• Inclusive and equal opportunity workplace with reasonable accommodations available.
• Comprehensive health, dental, and vision coverage.
• Retirement benefits, learning and development stipend, and generous paid time off.
• Equity compensation and potential commuter stipend for eligible roles.

Hiring process

• Compensation and level are determined during the interview process based on location, experience, qualifications, and interview performance.
• Candidates may be reconsidered for the same role after a 90-day waiting period.