Senior Product Manager

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 the backlog, sprint cadence, and the adoption outcomes for that workstream, partnering with a Principal Product Manager or engagement lead on the broader program.

You will work directly with client stakeholders and a delivery team of 5+ engineers and designers, making trade-offs daily about scope, sequencing, and what's worth shipping in the next sprint. If you've shipped AI products that actually move metrics - this is the role.

WHAT YOU'LL 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.
• You'll execute with clarity and pace - the engineers and designers on your workstream take cadence from you.

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

WHAT WE NEED FROM YOU
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 Product Management - 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 Product Managers
• Worked with knowledge graphs, semantic web, or rules-engine products
• Contributed to internal AI product playbooks or best practices