Forward Deployed Product Manager (SF/NY)

The Role

Our customers come to us with ambitious, often fuzzy goals. They want new AI capabilities (agents, workflows, skills) built on messy proprietary data that hold up at scale, and they often can't yet say what success looks like.

Your job is to turn those goals into AI-powered solutions that work in the real world, and to own the journey from project kickoff to live system to a tangible business outcome, not just a demo.

This is a technical, hands-on product role. You work directly in the AI systems you build with our engineering team: you prototype early, work with the data, run evals, and help hill-climb on quality. You make product-level technical calls yourself and act as a thought partner to the lead engineer on architecture, weighing short-term velocity against long-term extensibility.

You also work directly with clients. You build trust with their stakeholders and present the work to their leaders.

This is a forward-deployed, full-stack product role

• Part product manager: you decide what we build and why.
• Part builder: you prototype fast and get hands-on in the AI systems alongside our engineering team.
• Part delivery manager: you keep execution on track and keep client stakeholders aligned on progress, risks, and tradeoffs.
• Part "do whatever it takes" operator: you jump into the gaps to keep things moving.

What You’ll Do

• Shape what we build and why. Translate ambiguous business problems into crisp problem statements, user journeys, and success metrics, and work with customers to define what "success" actually means.
• Turn messy problems into shipped solutions. Translate ambiguous needs into clear requirements and PRDs, and run planning with engineers. Bring focus to define what good looks like for an AI system, then the drive to get it there.
• Prototype to discover and derisk. Build working prototypes early to learn what users need and to surface the hardest technical risks before the engineering team commits to a build.
• Build the ground truth. Work with client experts to assemble and label the ground-truth data that defines correct behavior for an AI system. Check it for coverage, consistency, and gaps, and plan how it gets maintained and extended.
• Hill-climb quality with the engineering team. Work with engineers on prompts, context design, and evals for the AI systems you build together. Run offline evals against ground truth during development and online evals on live traffic after launch. Read the failures, propose the fix, and repeat until we hit production quality.
• Shape technical decisions. Make product-level calls on model choice, retrieval and agent design, context management, and build vs. buy, and own the tradeoffs those calls carry for the project.
• Drive execution across multiple AI products. Run the day-to-day rhythm including planning, check-ins, risk tracking, and coordinating between clients, engineers, designers, and Ode teammates to keep work unblocked and on time.
• Drive adoption and long-term impact. Work with client teams on rollout and enablement so the systems you build actually get used. Bring back insights that inform Ode's playbooks and product direction.
• Bring judgment and clarity. When requirements are fuzzy or customers change course, be the person in the room who can say: here's what we're trying to do, here's what we know, here's the plan.
• Help build the team, not just the products. Own a team-wide initiative such as delivery playbooks, learning and development, or hiring. Experiment with AI tools and add what works to our shared PM toolkit.

What You Bring

• Real product and delivery experience. You've built and shipped products with engineers and designers across multiple cycles. You love to execute and are good at it. We typically look for 5+ years of experience in product management, engineering, or data science. However, we care more about what you've done than the label on your resume.
• Technical depth. You have a strong engineering, data, or technical PM background. You can whiteboard an end-to-end architecture, read a data schema and spot the problems, and use AI tools to build a medium-complexity system that holds up.
• AI fluency. You know how modern AI systems behave in practice. You know when retrieval beats agentic search, how to manage context across long multi-step tasks, when a reasoning model is worth the extra latency and cost, and where tool-using agents tend to break. You can explain these tradeoffs to a CTO and defend a design under technical questioning.
• Quantitative fluency. You can model out complex questions about a system with numbers: what it costs per transaction and how accuracy trades off against cost and latency. Your analysis is logical, easy to extend, and holds up to scrutiny.
• Client-facing acumen. You're the translation layer between novel technical concepts and business outcomes. You can run a working session with client stakeholders, present to their execs, and keep the relationship healthy as plans change. Client-facing or consulting experience is a strong plus.
• Structured problem-solving and communication. You ask sharp questions and turn a messy situation into a plan. You can whiteboard with an exec in the morning and write a precise spec for engineers in the afternoon. You communicate clearly and directly.
• Bias for action and ownership. You roll up your sleeves and make things happen, whether that's running your own data analysis, monitoring code quality with AI, shipping a prompt change, building a prototype, or jumping into a last-minute exec demo. When there's a gap in what you know, you close it yourself.
• Comfort with ambiguity and intensity. You like high-energy environments, messy problems, and "we haven't done this before" projects. You can juggle multiple projects, keep priorities straight, and make good calls with incomplete information.
• Intellectual humility and fast learning. AI moves fast, so your learning has to move with it. You say "I don't know, let me check" instead of overcommitting, and you don't let last quarter's assumptions about AI decide this quarter's design.
• Team-first mentality. High integrity, low ego, high agency. You lift others up and actively share best practices and seek to learn from others. You care about winning together.

How Ode Is Different

• Joining a services-first startup is an exciting transition.
• Unlike a traditional product company, you'll own two to three 0-to-1 products a year and learn from dozens more at the same time.
• You have outsized autonomy on each product, but you won't have a year to polish a single system.
• It's fast-paced, highly varied, keeps you on the frontier of models and tooling, and is the best way in the world to master applied AI product management.

Many PMs look back at this as the biggest growth period of their career. But it's possible you won't like it and we recommend using the interview process to hear what our team members think.

Benefits

• Competitive Compensation Package: Attractive salary aligned with your experience and skills.
• 401k with Matching: Invest in your future with our company-matched retirement plan.
• Unlimited PTO: Take the time you need to relax and rejuvenate.
• Exceptional Medical, Dental, and Vision Coverage: Comprehensive health benefits to keep you and your family healthy.
• Health FSA: Manage out-of-pocket health expenses effectively.
• Commuter Benefits: Make your travel to work easier and more affordable.
• Life Insurance: Providing peace of mind for you and your loved ones.
• Team Events and Activities: Regular events to build camaraderie and a strong team spirit.

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