AI Product Manager: Enterprise Data & AI Solutions

Ninjakitchen

Needham (MA)

On-site

USD 125,000 - 195,000

Full time

9 days ago

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Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Flexible spending accounts

Health savings accounts (HSA) with公司贡献

401(k) retirement plan with matching

Employee stock purchase program

Life insurance

AD&D

Short-term disability insurance

Long-term disability insurance

Generous paid time off

Company holidays

Parental leave

Identity theft protection

Pet insurance

Pre-paid legal insurance

Back-up child and eldercare days

Product discounts

Referral bonus program

Job summary

SharkNinja is seeking an AI Product Manager to own strategy, roadmap, and delivery for AI initiatives across the enterprise. You will translate business objectives into a clear backlog, collaborating with engineering and partners to deliver AI solutions that drive revenue growth and operational efficiencies. The role requires strong judgment on data foundations, build vs.

buy decisions, and governance. You’ll work with Global Data Product Management to ensure data quality and traceability across

Qualifications

5+ years in product management with shipped data or AI features tied to measurable outcomes.
Proven ownership of evaluation and experimentation for AI features (offline metrics, human/auto evals, and A/B testing).
Handson experiences driving application integrations at enterprise scale (APIled and iPaaS patterns, SLAs, data contracts, identity).
Demonstrated ability to lead build vs. buy decisions, supported by clear financial models and risk analyses.
Excellent executive communication and stakeholder leadership.

Responsibilities

Define a 3–9-month AI roadmap aligned to company strategic goals and value hypotheses.
Convert strategy into prioritized increments with PRDs, acceptance criteria, and release plans.
Own evaluation for AI features: offline tests, human and automated evals, online A/B experiments.
Define safety, privacy, and compliance requirements; implement guardrails with Security and Legal.
Define product requirements for API-first and event-driven integrations across CRM/ERP/eCommerce and data platforms.
Lead structured tradeoff analyses (TTV, TCO, vendor lock-in) and run proofs of value.
Lead squads spanning ML Engineering, MLOps, Data Engineering, Analytics, and Business stakeholders.
Define KPIs that connect outcomes to product performance and provide executive reporting.
Collaborate with Directors and Global Data Product Management to align standards and delivery.