Senior Product Manager · AI & Decision Intelligence

· AI Product / Enterprise Delivery · Onshore — US · 5+ Yrs Exp. · English Required · Full-Time

ABOUT HATCHWORKS AI

HatchWorks AI is an enterprise AI consulting firm. We design, build, and operate production-grade AI and software systems for clients across regulated and high-growth industries. Our teams pair senior architects and engineers with AI-assisted delivery methods to move clients from discovery to execution faster, without sacrificing rigor.

THE ROLE

Most product managers ship features. Few have shipped AI systems that operational users trust enough to use every cycle.

We're looking for a Senior Product Manager to own the product for a workstream inside one of our enterprise AI engagements — across forecasting, optimization, knowledge engineering, or user-facing interfaces. You will own backlog, sprint cadence, and the adoption outcomes for that workstream, partnering with a Principal PM or engagement lead on the broader program.

This is not a feature-list role. You will work directly with client stakeholders and a delivery team of five-plus engineers and designers, making trade-offs daily about scope, sequencing, and what's worth shipping in the next sprint.

US-based. Some travel to client sites and HatchWorks office locations may be required by engagement.

If you've shipped AI products that actually move metrics — this is the role.

WHAT YOU'LL ACTUALLY DO

Own product strategy for your workstream inside a multi-quarter enterprise AI engagement — from discovery through steady-state.
Own adoption success criteria for your workstream — the structured measures that determine whether the system is actually being used, not just shipped. You instrument them and report on them to the engagement lead.
Run discovery — operator interviews, SME workshops, behavior-pattern analysis. Convert tribal knowledge into shippable requirements.
Contribute to structured-feedback taxonomies with users and SMEs — the vocabulary that turns every user override into a model-retuning signal.
Manage the backlog for your workstream — within forecasting, optimization, knowledge engineering, or user-facing UIs. Sequence ruthlessly.
Day-to-day contact for your workstream — regular working relationship with business leads, SMEs, and operators.
Partner with the client's product counterpart on your workstream — build trust, share context, support ownership transfer.
Run sprint cadence — two-week sprints, sprint reviews, and reporting into the engagement's steering cadence.
Trade off ruthlessly — cut scope that doesn't move the metric. Defer complexity until the data rewards it. Right-size investment.
Flag Phase 2 opportunities to the engagement lead — additional scope, new use cases within your workstream. The engagement doesn't end; it converts.
Operate with consulting rigor — build credibility fast with new stakeholders, adapt your working style to each client's culture and tools, and turn ambiguity into a structured recommendation you can defend in the room.

THE TECHNICAL BAR

You will be expected to execute hands-on technical work from day one. The requirements below reflect the actual skills needed to deliver outcomes for enterprise clients.

Must-Haves

Enterprise PM — 5+ years shipping products inside mid-size to Fortune 500 enterprises
AI / ML Product — 2+ years working on AI products in production — recommendation systems, forecasting, optimization, NLP
Operational Software — Built products for operational users (planners, schedulers, ops teams) — not consumer apps
Stakeholder Range — Comfortable engaging business leaders and individual operators in the same week
Backlog & Cadence — Run sprint-level delivery for a workstream; defensible prioritization under pressure
Data Literacy — Read model outputs, understand calibration, interpret optimization results
Discovery Practice — Experience running structured discovery — interviews, shadowing, workshop facilitation
Vendor / Partner Coordination — Comfortable in multi-vendor environments — SI partners, internal platform teams
Consulting Experience — Proven track record working as an external consultant or in a client-services model — building trust quickly, managing ambiguity, and adapting across client environments

Core Tech Stack — Tools & Methods

Methods — Continuous discovery · Outcome-based roadmapping · RICE / WSJF prioritization
Cadence — Scrum · Shape Up · Adapted hybrid models
Tools — Notion · Linear / Jira · Miro / FigJam · Loom
Analytics — Mixpanel · Amplitude · SQL competence
Adjacent — Figma literacy · Comfort reading code and reviewing PRs

NICE TO HAVE

Experience mentoring or supporting junior PMs
Worked with knowledge graphs, semantic web, or rules-engine products
Contributed to internal AI product playbooks or best practices

WORKING CONTEXT

US-based. Some travel to client sites and HatchWorks office locations may be required by engagement.

You'll execute with clarity and pace — the engineers and designers on your workstream take cadence from you.

THE HUMAN BAR

Cadence skill is necessary. Outcome obsession is the differentiator.

The product managers who thrive here cut scope that doesn't move the metric — and they're willing to defend that decision to clients who want everything. They run delivery like a craft, and they treat adoption as the only acceptable definition of done.

Outcome obsession — ship-feature is not a goal. Move-metric is. You distinguish between the two every day.
Ruthless prioritization — every sprint is a series of trade-offs. You make them, you defend them, you adjust them.
Operator empathy — you spend time with the people who'll use what you ship. Tribal knowledge becomes spec.
Delivery ownership — you own your workstream from discovery to handoff, in partnership with the engagement lead.

WHAT MAKES THIS DIFFERENT

Most product roles ship inside a single company. This one ships across multiple enterprise clients over time — each with its own stakeholders, platforms, and constraints. You'll learn faster than is comfortable.

You will be embedded with a major global enterprise client — operating in supply chain, logistics, manufacturing, or adjacent operational industries — building production AI systems that decision-makers actually use.

You will work alongside ML engineers, optimization engineers, knowledge engineers, designers, and architects, partnering with a Principal PM or engagement lead on the broader program. Your job isn't to push tickets — it's to make your slice of the team faster, sharper, and more accountable to outcomes.

YOU'LL WORK INSIDE A PROPRIETARY AI DELIVERY FRAMEWORK

Most teams using AI tools today are flying blind — they feel faster but can't prove it. We built GenDD (Generative Driven Development) to change that, and you'll be working inside it from day one.

GenDD is a proprietary methodology and toolset built around one belief: great engineers need full context to move fast without breaking things. So we built the tools to give them exactly that.

Zero Ramp-Up

Our tooling surfaces full project context — architecture, data flows, history — so you hit the ground running on every engagement.

Proven Value

GenDD instruments every agent interaction, commit, and deploy — turning your work into clear, client-ready evidence of real impact.

All-In Team

Everyone here uses agents seriously. You're not evangelizing — you're exploring. We learn fast, share everything, and enjoy the work.

This is the environment technologists thrive in: structured methodology, tooling that solves real problems, teammates who move at pace, and clients who care about the results.

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