Lead AI Product Manager Retirement & finance and insurance Domain

Key Requirements Summary

• 8+ years in Product Management
• 4+ years leading AI/ML product initiatives
• Proven ownership of AI products from ideation to production rollout
• Experience defining product strategy and roadmap independently
• Strong stakeholder management with VP/C-level influence
• Experience working in regulated industries (financial services preferred)

Core AI/Technical Skills (Must Have)

Candidates should have practical, production-level AI product experience in:

• LLM-based applications using:
  • GPT-4o
  • Claude
  • Gemini
• Prompt engineering & structured outputs
• RAG architecture understanding:
  • chunking
  • embeddings
  • retrieval optimization
  • hallucination mitigation
• Agentic AI workflows:
  • LangChain
  • LangGraph
  • Vertex AI Agent Builder
  • Copilot Studio
• AI evaluation frameworks:
  • precision/recall
  • ROC-AUC
  • hallucination metrics
• SQL/data fluency
• API/system architecture understanding
• AI experimentation:
  • A/B testing
  • cohort analysis
  • shadow deployments
• Daily usage of AI developer tools:
  • GitHub Copilot
  • Cursor
  • Claude Code

Mandatory Retirement & Wealth Domain Expertise

Strong hands-on knowledge required in:

• 401(k), 403(b), 457 plans
• SECURE 2.0 regulations
• ERISA & fiduciary standards
• Retirement readiness and participant behavior
• Target-date funds & managed accounts
• Advisor ecosystem:
  • RIA
  • Broker-dealer
  • Recordkeepers

Preferred Certifications

• CFP
• CFA
• CEBS
• CRPS
• ASPPA (QKA/QPA)

Ideal Candidate Background

Best-fit candidates likely come from:

• Retirement recordkeepers
• Wealthtech/fintech firms
• Asset management companies
• RIA platforms
• AI innovation labs within financial institutions

Strong Matching Titles

• Lead AI Product Manager
• Principal Product Manager AI
• Director Product Management GenAI
• AI Platform Product Lead
• WealthTech Product Manager
• Retirement Digital Product Lead