Who You AreThis is a player-coach manager role. You will own execution directly and build the AI product and engineering function over time, starting with a small team reporting to you. You define direction by shipping, not by delegating.
You have taken AI products from idea to production and understand how to work across data, models, and product constraints to ship reliably. You are strong on the data engineering side and can reason about pipelines, schemas, and data quality as naturally as you reason about model outputs. You can write a sharp product spec, pressure-test an ML pipeline with an engineer, and explain the tradeoffs to an executive in the same afternoon.
You ship fast and make pragmatic decisions about when to build versus leverage third-party solutions, balancing speed, cost, and long-term capability. You are comfortable operating in ambiguity and working with imperfect data and evolving systems without slowing down execution. You have managed or mentored AI engineers and data engineers and know how to get the best out of a small technical team.
What You Will OwnYour scope from day one includes:
- AI product strategy and roadmap across document intelligence, workflow automation, and data-driven decisioning, with our mortgage Point of Sale as the flagship integration surface
- Direct management of AI engineers and data engineers, setting direction, removing blockers, and developing the team
- Deep AI integration into the POS, ensuring AI capabilities are embedded in the borrower and loan officer experience rather than sitting alongside it
- Coordination across AI and data engineering to design, scope, and ship production systems at speed
- Peer relationships with Product, Engineering, and Customer Experience, keeping AI aligned with the rest of the product surface
- Vendor and model evaluation against cost, performance, and build vs. buy considerations
- Feature intake and prioritization, including how AI feature requests are evaluated, sequenced, and delivered
Must haves- 8+ years in product management, with at least 3 years focused on AI/ML products in production
- Demonstrated experience shipping AI-powered features end-to-end, from problem definition through model deployment and evaluation
- Experience managing or mentoring AI engineers or data engineers directly
- Strong technical fluency: Can read API docs, evaluate model outputs, and collaborate with ML engineers without a translator
- Strong data engineering fluency: Can reason about pipelines, schemas, data quality, and the infrastructure AI products depend on
- Experience with LLM-based systems, including prompt design, RAG architectures, document intelligence, or similar
- Track record of shipping AI features quickly, with a bias for learning through production deployment
- Writes crisp product specs, leads cross-functional reviews, and presents to executives
- Proven ability to manage peer relationships across Product, Engineering, and Customer Experience
- Data-driven prioritization discipline: Knows how to evaluate impact, weigh tradeoffs, and say no
Nice to haves- Fintech, mortgage, or regulated industry experience
- Awareness of how AI systems operate in regulated environments and how that impacts product design
- Familiarity with AWS cloud AI services (Bedrock, SageMaker) or equivalent cloud AI platforms
- Experience with document AI including classification, extraction, completeness, or verification workflows
- Hands-on familiarity with modern data warehouses (Snowflake, BigQuery) and transformation tools (dbt)
- Product analytics tools (PostHog, Pendo, Mixpanel) and SQL proficiency
- Experience scaling a small AI product or engineering function
What Success Looks Like- A clear AI product roadmap exists and is being executed against within 90 days
- AI capabilities embedded in the POS are measurably more accurate, reliable, and cost-efficient within 180 days
- AI engineers and data engineers are productive, unblocked, and shipping
- Product, Engineering, and Customer Experience are aligned on what AI can and cannot do, and why
- Feature intake has a defined process
- Leadership turns to you for clear, real-time visibility into what's happening in AI
Salary Band: $90,000 - $150,000 (depending on experience and location)
