AI Product Manager

About the role

We’re hiring an AI Product Manager to build the next generation of investor-facing products powered by AI.

Sit on the Public Investor team, owning products that help institutional investors turn complex data into faster, higher-conviction decisions. This includes AI-powered workflows across:

• MCPs (Model Context Platforms)
• AI agents for research and analysis
• Investor-facing portal experiences
• Data feeds and programmatic access

Key Responsibilities

• Own AI product strategy for investor workflows: Define how AI transforms the way public market investors consume, analyze, and act on data.
• Build AI-native products, not just features: Design end-to-end experiences across agents, copilots, and structured outputs, not just UI layers on top of models.
• Translate frontier AI into real-world utility: Evaluate and integrate LLMs, retrieval systems, and agent architectures into production-grade products.
• Work directly with customers: Partner with hedge funds and asset managers to deeply understand workflows, pain points, and trust requirements.
• Drive rapid experimentation and iteration: Run tight feedback loops across prompts, evals, and product UX to continuously improve performance and usefulness.
• Collaborate across disciplines: Work closely with engineering, data, research, and design to ship high-quality, high-impact products, while communicating clearly with both technical and non-technical partners.
• Define quality, reliability, and trust: Establish evaluation frameworks for AI outputs, ensuring accuracy, consistency, and investor-grade reliability.
• Shape the future of the platform: Contribute to how MCPs, agents, and APIs evolve into a unified, reliable, and safe AI product ecosystem.

Qualifications & Skills

• 4-6+ years of product management or similar experience.
• Experience building AI copilots, agents, or internal AI tools
• Familiarity with how AI/ML models and AI agents are built and maintained.
• Strong product instincts with a track record of building 0→1 or ambiguous products
• Strong user research and customer discovery skills with deep curiosity about AI systems (LLMs, agents, retrieval, evals)
• Generalist knowledge of both engineering and design.
• Able to design and evaluate prompts, contexts, and model behaviors.
• Analytical thinker, comfortable with data and experimentation.
• Great communicator and collaborator.
• High ownership mindset with a bias toward action and learning

Nice to Have

• Familiarity with financial markets or investor workflows
• Experience with data platforms, APIs, or developer-facing products
• Background in analytics, research, or quantitative environments