Product Manager
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Job Description
Product Manager building governed agentic AI decisioning and automation products for banks and insurers. Owning roadmaps, evaluation harnesses, and regulated enterprise deployments.
Responsibilities:
- Take agentic automations from concept to a product line
- Own roadmap, prioritisation, OKRs, and outcomes for lead categorization and scoring, lead-to-advisor matching, and renewal and cross-engagement opportunity detection
- Define the governance harness for agentic AI, including autonomy boundaries, human-in-the-loop requirements, audit trails, and evaluation gates
- Work with compliance and engineering leadership on AI governance
- Design autonomous capabilities within regulatory constraints for banking and insurance clients
- Define automation capabilities and collaborate with peer product management and platform engineering on shared infrastructure
- Understand enterprise BFSI distribution workflows, agency structures, and compliance constraints and translate them into products
- Lead a squad of engineers and a designer to ship and iterate quickly while maintaining safety and evaluation standards
- Use AI tooling to increase productivity
- Use data to measure match quality, opportunity-detection precision, advisor adoption, and downstream conversion
- Establish priorities, outcomes, success measures, and foundations for evaluating and governing agentic capabilities
- Continuously improve automation quality and impact using data and customer outcomes
Requirements:
- Built and shipped LLM-powered decisioning or automation systems in practice, including tool use, orchestration, structured outputs, and evaluation design
- Built evaluation harnesses, guardrails, human review workflows, and audit evidence for trustworthy AI decisions
- Sound judgment about autonomy in high-stakes settings; able to determine when AI should act, recommend, or hand off to a human and defend that reasoning to compliance officers
- Fluency with prompting, retrieval, and evaluation
- Uses AI tooling by default and can demonstrate it
- Thrives in ambiguity and takes ownership independently
- Communicates clearly and concisely in writing and in person across technical, commercial, and compliance audiences
- Deep domain knowledge in insurance, wealth management, or financial services sales and servicing (nice-to-have)
- Enterprise SaaS experience, especially deploying into large regulated institutions (nice-to-have)
- Experience with lead management, CRM intelligence, sales operations tooling, or recommendation and matching systems (nice-to-have)
- Familiarity with AI governance frameworks in financial services, such as MAS FEAT or HKMA GenAI guidance (nice-to-have)
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