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January

Senior/Staff Product Manager, AI Agents

Reposted 2 Days Ago
Hybrid
New York City, NY
185K-244K Annually
Senior level
Hybrid
New York City, NY
185K-244K Annually
Senior level
The Staff Product Manager will lead AI agent strategy, defining product vision and quality, maximizing revenue impact, and shaping how the company operates with AI.
The summary above was generated by AI

At January, we're transforming the lives of consumers by bringing humanity to consumer finance. Our data-driven products help financial institutions streamline their collections, offering borrowers straightforward and compassionate solutions to regain financial stability and control over their lives. We're not just expanding access to credit – we're restoring dignity and giving millions of people the chance to achieve financial freedom.

About the Role

We're building AI agents that don't just assist — they act. Autonomously. At scale. Across the most consequential moments in our product. This role owns the strategy, quality, and business impact of that system — and defines how the entire company builds with AI going forward.

You'll architect how AI agents reason, decide, and execute across complex workflows — then build the systems that make them reliable, measurable, and continuously improving. You'll pressure-test our assumptions about what agents can become, bring product rigor to a domain where we've been moving fast without it, and set the standard other PMs learn from.

We have early traction and strong conviction. What we need is a staff PM who turns that into a platform — one that expands what AI agents can own, accelerates how fast we ship them, and fundamentally changes our unit economics.

What You'll Own

The AI agent strategy. You own the roadmap. Not a feature backlog — a sequenced, opinionated strategy tied directly to business outcomes. You'll decide what we build, what we buy, and when we switch vendors as the landscape shifts. You'll identify product, technical, and regulatory constraints 6–12 months out and architect around them before they become blockers. Product, Engineering, Operations, and GTM leadership will look to you as a sparring partner, someone who challenges assumptions and pushes the engagement strategy to be more ambitious through AI agents.

Agent quality and the pace of iteration. You'll define what "good" looks like for our AI agents across prompt engineering, conversation design, and real-world performance, and build the evaluation frameworks to measure it. You own the full agent UX: conversation flows, authentication, multi-topic handling, all designed for user trust and measurable conversion outcomes. You'll partner with Legal and Compliance to build patterns that keep us compliant without slowing us down.

Revenue impact. You'll prioritize the campaigns and workflows that maximize operational efficiency while driving incremental revenue. You'll partner with GTM to expand adoption across segments and turn agent performance into top-line growth.

How the company builds with AI — beyond this role. You'll create the playbooks, evaluation frameworks, prompt engineering standards, vendor assessment criteria, that let other PMs ship AI features without you in the room. You'll build organizational AI fluency across Operations, GTM, Legal, and leadership so the company makes better decisions about where AI fits.

What We're Looking For
  • AI Strategy: Defines compelling product vision and translates it into sequenced, high-conviction bets. Makes principled trade-offs that others adopt as decision frameworks.

  • AI/LLM Product Craft: Deep product intuition for building with LLMs, conversation design, prompt engineering, evaluation. Stays ahead of the landscape and translates shifts into product decisions before the market catches up.

  • Technical Depth: Partners with engineering on infrastructure and architecture trade-offs. Reasons about latency, cost, API design, and observability at the level engineers respect.

  • Analytical Rigor: Defines what "good" looks like for AI systems through quantitative and qualitative evaluation. Structures experiments that accelerate learning.

  • Truth-Seeking: Pressure-tests assumptions, including your own. Seeks disconfirming evidence before committing. Delivers uncomfortable truths with clarity.

  • Collaboration & Influence: Drives alignment across Product, Engineering, Legal, Operations, GTM, and clients. Translates complex AI concepts for diverse audiences.

  • Ownership & Velocity: Takes on ambiguous problems before being asked. Moves fast with incomplete information. Ships and iterates rather than perfecting.

Experience

Required

  • 8+ years of product management with demonstrable expertise building AI/LLM-powered products — conversational AI, AI agents, or similar

  • Hands-on experience with prompt engineering, LLM evaluation frameworks, and conversation design (not just managing engineers who do this work)

  • Track record of strategic build-vs-buy decisions for AI infrastructure

  • Experience shipping in ambiguous, rapidly evolving technical domains

  • Strong technical fluency — comfortable discussing system architecture, API design, and latency/cost trade-offs with engineers

  • 0→1 product experience building and commercializing new capabilities

Preferred

  • Experience building conversational AI at scale at a high-growth company

  • Familiarity with AI agent platforms and their trade-offs

  • Experience coaching other PMs on AI best practices

We encourage you to apply if you value:
  • Collaborative Ownership beats Fiefdoms. You step into gaps without being asked. You fix issues. You seek to bring in the right people.

  • Speed beats perfection. You make decisions with incomplete information, iterate quickly, and course-correct based on what you learn. Fast loops beat slow ones.

  • Candor beats comfort. You give direct feedback because you care about people's growth. You'd rather hear a hard truth early than a polite sidestep that wastes time. Example: Last quarter, an engineer told our CEO his proposed timeline was unrealistic in a company-wide meeting — and was thanked for it.

  • Inputs beat outcomes. You evaluate decisions by the thinking behind them, not just results. Good process increases the odds; bad outcomes don't always mean bad decisions.

  • Why beats what. You diagnose before prescribing. You're more interested in root causes than symptoms, and you share context so others can make good decisions without you.

  • Writing beats meetings. You structure your thinking on paper. You know that clarity scales and that a well-written doc often accomplishes more than an hour-long meeting.

--

We are currently hiring for this position in our New York office.

As a New York City-based company, we are dedicated to transparent, fair, and equitable compensation practices that reflect our commitment to fostering an environment where all team members are valued and supported. We encourage individuals from all backgrounds to apply.

We are an equal opportunity employer committed to diversity and inclusion in the workplace. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, age, veteran status, or any other legally protected characteristic.

Top Skills

AI
Conversational Ai
Llm
Prompt Engineering

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