About the Role
You will own the strategy and roadmap for AI powered risk automation products. You will identify AI opportunities grounded in user needs and measurable business value. Translate ambiguous problem spaces into clear product requirements. You will work closely with ML engineers, data scientists, and researchers on model goals, data needs, evaluation methods, and quality gates. You will build and run experiments to validate hypotheses and iterate quickly. You will define how the product should behave across success, failure, and edge cases. You will establish metrics for accuracy, safety, latency, reliability, and UX satisfaction. You will partner with design on intuitive, transparent, and safe human AI interactions. You will collaborate with legal, security, and compliance teams to ensure responsible AI practices. You will lead cross functional execution from concept through launch and iteration.
Requirements
- 6-9 years of product management experience including a proven track record launching successful AI or ML driven products
- Strong technical intuition about ML models training loops evaluation prompt design data pipelines and real time inference constraints
- Experience designing and running structured experiments including A/B tests and offline evaluations
- An ownership mentality with the ability to rapidly drive complex cross functional initiatives from strategy through execution at scale
- Excellent communicator capable of distilling complex technical concepts into clear narratives for executive operational and technical audiences
- Ability to work across scaled risk compliance and operational teams in a regulated industry
- Familiarity with AI quality safety and responsible use frameworks
- Experience with LLMs multimodal models or applied generative AI
- Experience building operational tooling that drives cost savings and quality
Responsibilities
- Own the strategy and roadmap for AI powered products and capabilities
- Identify AI opportunities grounded in user needs and measurable business value
- Translate ambiguous problem spaces into clear product requirements
- Work closely with ML engineers, data scientists, and researchers on model goals, data needs, evaluation methods, and quality gates
- Build and run experiments to validate hypotheses and iterate quickly
- Define how the product should behave across success, failure, and edge cases
- Establish metrics for accuracy, safety, latency, reliability, and UX satisfaction
- Partner with design on intuitive, transparent, and safe human AI interactions
- Collaborate with legal, security, and compliance teams to ensure responsible AI practices
- Lead cross functional execution from concept through launch and iteration
Benefits
- Remote work
- Medical insurance
- Flexible time off
- Retirement savings plans
- Modern family planning