Compensation: $139-196k Base + Bonus + Benefits + Options
Location: Remote with travel to Denver, CO Area ~6 times per year
Remote Eligibility: CA, DC, FL, GA, IL, IN, MN, MS, NC, NV, NY, OH, OR, PA, SC, TN, TX, VA, and WA
Responsibilities
- Own and execute the roadmap for core payment capabilities, partner integrations, platform services, and AI-powered experiences.
- Translate customer needs, market signals, and technical constraints into prioritized requirements, user stories, and acceptance criteria.
- Work directly with engineers during discovery, sprint planning, backlog refinement, technical design, testing, and production releases.
- Apply payments expertise to product visions (particularly virtual cards, accounts receivable, ACH, interchange, settlement, and payment networks)
- Identify and deliver practical AI use cases across internal efficiency, revenue growth, and customer-facing products.
- Define expected behavior, evaluation criteria, guardrails, human oversight, and acceptable failure modes for AI-powered features.
- Use advanced AI development tools, including Claude Code or similar platforms, to create prototypes, agents, automations, and product-management workflows.
- Partner with data and engineering teams on data migrations, payment-data products, analytics, and modern platforms such as Snowflake.
- Make informed build-versus-buy-versus-partner recommendations based on speed, cost, differentiation, and risk.
Qualifications
- 7+ years of experience in technical product management.
- Meaningful payments or fintech experience; knowledge of virtual card payments and accounts-receivable workflows is especially important.
- Recent hands‑on involvement in substantive AI initiatives in the past 12 months.
- Experience using Claude Code or similar AI development tools to build, prototype, or automate workflows—not solely basic tools such as Microsoft Copilot.
- Experience shipping AI-, ML-, or LLM-enabled products, features, agents, or internal capabilities.
- Strong understanding of APIs, integrations, system architecture, cloud platforms, and CI/CD practices.
- Working knowledge of LLMs, RAG, agents, embeddings, model evaluation, and cost, latency, quality, and safety trade-offs.
- Strong data background, ideally involving migrations, Snowflake, payment data, reconciliation, or modern data platforms.
- Comfortable navigating codebases and technical documentation; the ability to contribute code, automations, or pull requests is a significant advantage.