AI Product Management Senior Manager

Senior Manager

Position Summary The Senior Manager, AI Product Management will lead the end-to-end strategy, planning, and delivery of AI/ML products and capabilities. This role is accountable for portfolio outcomes, cross-functional alignment, and adherence to responsible AI and compliance standards while mentoring a team of product managers.

Primary Responsibilities

• Define the AI product strategy and roadmap aligned to business objectives and user needs.
• Prioritize initiatives based on ROI, feasibility, data readiness, and risk.
• Lead discovery, proof-of-concept and pilot initiatives, and general availability launches with clear stage gates.
• Partner with Data Science and Engineering on model lifecycle, evaluation, performance (latency/cost), and reliability (SLA/SLO).
• Establish robust observability: data and model drift, quality metrics, safety and hallucination monitoring, and feedback loops.
• Ensure compliance with privacy, security, and regulatory requirements (e.g., PII, GDPR/CCPA, SOC 2, and domain-specific standards).
• Drive cross-functional alignment with Design, Legal/Privacy/Security, Marketing, Sales, Customer Success, and Operations.
• Manage and develop product managers; set objectives, provide coaching, and support career progression.
• Lead go-to-market efforts including positioning, packaging, pricing, and field enablement.

Minimum Qualifications

• 7–10+ years of product management experience, including 4+ years in AI/ML or data products and 2+ years managing product managers.
• Demonstrated success delivering AI/ML or GenAI products at scale.
• Proficiency in AI/ML concepts (LLMs, RAG, agents, evaluation) and MLOps practices.
• Quantitative aptitude, including experiment design, metrics, and basic SQL; strong written and verbal communication.
• Experience with privacy, security, and responsible AI practices.

Preferred Qualifications

• Industry expertise in [e.g., financial services, healthcare, commerce, enterprise SaaS].
• Familiarity with modern AI infrastructure (vector databases, orchestration frameworks, GPUs) and cost/latency optimization.
• Experience with major cloud providers (AWS/GCP/Azure), data platforms (Snowflake/Databricks), and observability tools.
• Exposure to safety testing, red teaming, and content moderation.
• Advanced degree (MBA or technical field) preferred.

Key Performance Indicators

• Business outcomes: revenue impact, conversion/retention, cost-to-serve, time-to-resolution.
• Product performance: adoption, activation, satisfaction (CSAT/NPS).
• AI quality: accuracy, hallucination rate, drift metrics, latency (p95), and cost per request.

Initial 30-60-90 Day Objectives

• 30 Days: Assess portfolio, data readiness, metrics, and risks; conduct stakeholder and customer discovery; identify priority opportunities.
• 60 Days: Deliver a staged roadmap; establish evaluation and monitoring frameworks; align go-to-market plans.
• 90 Days: Launch initial pilot/GA; operationalize monitoring and feedback mechanisms; publish governance artifacts