Machine Learning and AI Opportunities

About Us

SharkNinja is a global product design and technology company with a diversified portfolio of 5-star rated lifestyle solutions that positively impact peoples lives in homes around the world. the company has a proven track record of bringing disruptive innovation to market and developing one consumer product after another has allowed SharkNinja to enter multiple product categories driving significant growth and market share gains. Headquartered in Needham Massachusetts with more than 3600 associates the companys products are sold at key retailers online and offline and through distributors around the world.

Note: This is a Pipeline Opening and Not Tied to A Specific Opening

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 impactful 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

Area

What Youll Own

Product Strategy & Vision

Define a 39-month AI roadmap aligned to company strategic goals with clear problem statements and value hypotheses to maximize value.

Portfolio & Roadmap

Convert strategy into prioritized increments with PRDs acceptance criteria and release plans; keep a transparent backlog.

Evaluation & Experimentation

Own evaluation for AI features: offline tests human and automated evals 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..

CrossFunctional 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.

Required 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.

Preferred Qualifications

• 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 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 exec approval.
• AI initiatives deliver a minimum 5x ROI on Capex investments contributing directly to revenue growth.