Director, Product Management (Data & Agentic AI Platform)

Achieve is a leading digital personal finance company. We help everyday people move from struggling to thriving by providing innovative, personalized financial solutions. By leveraging proprietary data and analytics, our solutions are tailored for each step of our member’s financial journey to include debt consolidation, personal loans, home equity loans, financial tools and education. Every day, we get to help our members move their finances forward with care, compassion, and empathetic touch. We put people first and treat them like humans, not account numbers.

The fintech industry is large and growing. Over $11T in home equity is sitting untapped across US homeowners - most haven’t borrowed against it yet, while personal loan balances just hit a record $276Bn from four years in a row of growth, with no signs of slowing. Consumers continue to face mounting debt. Credit card delinquencies are up 38%, leading to more demand for debt relief services. Achieve continues to support members and meet them wherever they are on their journey. Since 2002, Achieve has grown into one of the largest private consumer fintech unicorns in the U.S., with over $57B in enrollments for our industry-leading, tech-enabled debt resolution services business, and over $16Bn in personal and home loans originations.

Job Description About this role: Achieve is redefining how customers experience financial help and its internal operating model, with AI at the center rather than bolted on. We’re looking for a Director of Product Management to own the two foundational enterprise capabilities that make that possible:

• Data Platform - the governed data foundation and semantic layer that enable agentic workflows, natural language analytics and standardized reporting, along with the enterprise consumer data products built on it
• Agentic AI Platform - the shared harness and infrastructure that lets teams across Achieve build, launch & govern their own workflows and customer-facing agents

This is initially a hands-on senior individual contributor role: you will define the platform strategy and roadmap, inform the early technology and vendor choices and work alongside engineering, data, security, risk, compliance teams to get both platforms launched and operating at scale. As the platforms mature and become more embedded into the business, we expect this role grows into a team leadership position.

Why this role matters: A shared platform foundation enables AI at Achieve to operate at scale, so that every new agent, voice experience, and analytics capability benefits from what came before. Agents are faster to build, cheaper to operate, safer to run and better informed because they share data, context, learnings and governance. The choices made by this leader early on will shape how Achieve builds and operates for years. Done well, this role will:

• Replace static dashboards and traditional BI reports with a real-time end-to-end view of the business, where people can ask questions in plain language and get trusted answers
• Deliver the governed data foundation and shared agent harness that let teams design, launch, measure, and govern their own AI-driven workflows
• Help teams rethink how they operate around agents, with guardrails that scale with risk, in a regulated industry where trust and auditability are non-negotiable

What You’ll Do Data Platform

• Define and execute strategy for the enterprise data platform, including target architecture, sequencing, and success metrics
• Lead migration of existing data, ETL processes, and dashboards with minimal business disruption
• Optimize replication, storage, and compute to materially reduce inefficiencies and cost
• Own the roadmap for the enterprise data products and services across identity, consent, product interaction and insights that are leveraged by multiple product teams
• Enable agentic and natural language analytics so business users can self-serve trusted insights

Context Engineering & Semantics

• Own the enterprise semantic layer and business glossary: governed definitions that serve both BI users and agents
• Define how agents get the right information, tools, instructions, and memory for each task, and how that context is assembled, versioned, tested, and kept current
• Set standards for measuring context quality, including retrieval accuracy, grounding, freshness, and cost
• Define access models so agents see only what each user and…