Ninjakitchen
Machine Learning and AI Opportunities
Ninjakitchen, Needham Heights, Massachusetts, us, 02494
SharkNinja is a global product design and technology company with a diversified portfolio of lifestyle solutions. Powered by two trusted, global brands, Shark and Ninja, the company has a track record of bringing disruptive innovation to market and expanding into multiple product categories. Headquartered in Needham, Massachusetts with more than 3,600 associates, the company’s products are sold worldwide.
Overview This pipeline opening is not tied to a specific opening.
AI Product Manager – responsibilities The AI Product Manager owns strategy, roadmap, and delivery for AI initiatives across the enterprise. This role translates business objectives into a clear prioritized backlog, collaborating with engineering teams and external partners to deliver solutions that drive measurable business impact through revenue growth or new operational efficiencies. The Product Manager works closely with Global Data Product Management, including Data and MDM, to ensure AI products are built on trusted, standardized data foundations. The role requires strong judgment in application integrations and build vs. buy tradeoffs, balancing speed, cost, and enterprise standards.
Key Responsibilities
Define a 3–9-month AI roadmap aligned to company strategic goals, with clear problem statements and value hypotheses to maximize value.
Convert strategy into prioritized increments with PRDs, acceptance criteria, and release plans; maintain a transparent backlog.
Own evaluation for AI features: offline tests, human and automated evaluations, and online A/B experiments to optimize quality, latency, and cost effectiveness. Publish decision logs for model, prompt, and dataset changes.
Responsible AI & guardrails: define safety, privacy, and compliance requirements; implement guardrails and review rituals with Security and Legal; ensure traceability of data, prompts, and outputs.
Application integrations: define product requirements for API-first and event-driven integrations across CRM/ERP/eCommerce and data platforms; align on data contracts, SLAs, auth/PII handling, and system observability with Platform teams.
Build vs Buy: lead structured tradeoff analyses (TTV, TCO, vendor lock-in, differentiation, compliance). Run proofs of value with vendors when needed and recommend paths forward, highlighting risks and contingency plans.
Cross-functional leadership: lead squads spanning ML Engineering, MLOps, Data Engineering, Analytics, and Business stakeholders; keep scope, risks, and dependencies visible.
Impact measurement: define clear KPIs that connect business outcomes to product performance, and provide executives with simple, actionable reporting against those targets.
Partnerships: collaborate with Director, ML and AI, Security, Legal, Procurement, and Global Data Product Management (Data and MDM) to align standards, governance, and delivery.
Qualifications
Required:
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).
Hands-on experience driving application integrations at enterprise scale (API-led 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.
Preferred:
Experience optimizing Amazon sales and ad channels.
Experience with Salesforce Cloud and CDP integrations.
Exposure to LLMOps practices (prompt versioning, guardrails, eval frameworks), vector search/RAG, or model observability.
Success Metrics (first 12 months)
AI roadmap approved and in execution within 90 days; at least two AI product increments shipped with adoption targets met.
Application integrations delivered on time with measurable data quality and reliability improvements.
At least two major technology decisions completed with a formal build vs. Buy analysis and executive approval.
AI initiatives deliver a minimum 5x ROI on Capex investments, contributing directly to revenue growth.
Culture and Benefits We offer competitive health insurance, retirement plans, paid time off, employee stock purchase options, wellness programs, product discounts, and learning programs. We empower your personal and professional growth with opportunities to redefine what’s possible. Diversity, equity, and inclusion are vital to our global success. We strive to create an inclusive workplace where all associates can bring their authentic selves to work and accelerate their careers.
EEO and Accommodation We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender identity, sexual orientation, age, marital status, veteran status, disability, or any other class protected by law. If you require a reasonable accommodation to participate in the job application or interview process, please contact SharkNinja People & Culture at accommodations@sharkninja.com
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Overview This pipeline opening is not tied to a specific opening.
AI Product Manager – responsibilities The AI Product Manager owns strategy, roadmap, and delivery for AI initiatives across the enterprise. This role translates business objectives into a clear prioritized backlog, collaborating with engineering teams and external partners to deliver solutions that drive measurable business impact through revenue growth or new operational efficiencies. The Product Manager works closely with Global Data Product Management, including Data and MDM, to ensure AI products are built on trusted, standardized data foundations. The role requires strong judgment in application integrations and build vs. buy tradeoffs, balancing speed, cost, and enterprise standards.
Key Responsibilities
Define a 3–9-month AI roadmap aligned to company strategic goals, with clear problem statements and value hypotheses to maximize value.
Convert strategy into prioritized increments with PRDs, acceptance criteria, and release plans; maintain a transparent backlog.
Own evaluation for AI features: offline tests, human and automated evaluations, and online A/B experiments to optimize quality, latency, and cost effectiveness. Publish decision logs for model, prompt, and dataset changes.
Responsible AI & guardrails: define safety, privacy, and compliance requirements; implement guardrails and review rituals with Security and Legal; ensure traceability of data, prompts, and outputs.
Application integrations: define product requirements for API-first and event-driven integrations across CRM/ERP/eCommerce and data platforms; align on data contracts, SLAs, auth/PII handling, and system observability with Platform teams.
Build vs Buy: lead structured tradeoff analyses (TTV, TCO, vendor lock-in, differentiation, compliance). Run proofs of value with vendors when needed and recommend paths forward, highlighting risks and contingency plans.
Cross-functional leadership: lead squads spanning ML Engineering, MLOps, Data Engineering, Analytics, and Business stakeholders; keep scope, risks, and dependencies visible.
Impact measurement: define clear KPIs that connect business outcomes to product performance, and provide executives with simple, actionable reporting against those targets.
Partnerships: collaborate with Director, ML and AI, Security, Legal, Procurement, and Global Data Product Management (Data and MDM) to align standards, governance, and delivery.
Qualifications
Required:
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).
Hands-on experience driving application integrations at enterprise scale (API-led 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.
Preferred:
Experience optimizing Amazon sales and ad channels.
Experience with Salesforce Cloud and CDP integrations.
Exposure to LLMOps practices (prompt versioning, guardrails, eval frameworks), vector search/RAG, or model observability.
Success Metrics (first 12 months)
AI roadmap approved and in execution within 90 days; at least two AI product increments shipped with adoption targets met.
Application integrations delivered on time with measurable data quality and reliability improvements.
At least two major technology decisions completed with a formal build vs. Buy analysis and executive approval.
AI initiatives deliver a minimum 5x ROI on Capex investments, contributing directly to revenue growth.
Culture and Benefits We offer competitive health insurance, retirement plans, paid time off, employee stock purchase options, wellness programs, product discounts, and learning programs. We empower your personal and professional growth with opportunities to redefine what’s possible. Diversity, equity, and inclusion are vital to our global success. We strive to create an inclusive workplace where all associates can bring their authentic selves to work and accelerate their careers.
EEO and Accommodation We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender identity, sexual orientation, age, marital status, veteran status, disability, or any other class protected by law. If you require a reasonable accommodation to participate in the job application or interview process, please contact SharkNinja People & Culture at accommodations@sharkninja.com
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