Generative AI Product Manager

Role & responsibilities

• Define and execute the product vision, strategy, and roadmap for Generative AI products and capabilities.
• Identify high-value customer and business problems that can be solved using LLMs, RAG, AI agents, and other GenAI technologies.
• Translate customer needs, business objectives, and technical capabilities into clear product requirements, PRDs, and prioritized roadmaps.
• Partner closely with AI/ML engineers, data scientists, software engineers, designers, UX researchers, and business stakeholders to build and launch AI products.
• Lead the end-to-end product lifecycle from discovery and ideation through development, launch, adoption, and continuous optimization.
• Evaluate LLMs, foundation models, AI platforms, APIs, vector databases, and emerging GenAI technologies to determine the right solution for each use case.
• Define AI product evaluation frameworks, success metrics, quality benchmarks, and experimentation strategies.
• Establish approaches for managing hallucinations, bias, model quality, safety, privacy, security, and responsible AI risks.
• Design and optimize user experiences for AI-powered features, including conversational interfaces, copilots, agents, and intelligent automation.
• Conduct user research, competitive analysis, market assessment, and customer discovery to identify product opportunities.
• Develop business cases, pricing strategies, ROI models, and go-to-market plans for GenAI products.
• Monitor product performance through adoption, engagement, retention, quality, latency, cost, and business-impact metrics.
• Drive experimentation, A/B testing, feedback loops, and continuous improvement of AI models and product experiences.
• Manage relationships with AI technology vendors, cloud providers, model providers, and strategic partners.
• Communicate product vision, progress, trade-offs, and business outcomes effectively to senior leadership and cross-functional stakeholders.

Preferred candidate profile

• 5 to 10 years of experience in Product Management, AI/ML Product Management, Technology Product Management, or a related role, with demonstrated experience taking products from concept to market.
• Strong understanding of Generative AI, LLMs, RAG, AI agents, foundation models, embeddings, prompt engineering, and AI application architectures.
• Proven experience building or managing AI-powered products or features with measurable customer or business impact.
• Strong product-management fundamentals including product discovery, roadmap planning, prioritization, PRD development, experimentation, product analytics, and lifecycle management.
• Ability to translate complex AI/technical concepts into clear product requirements and customer-focused solutions.
• Experience working closely with ML engineers, data scientists, software engineers, UX/design teams, and business stakeholders.
• Strong understanding of AI evaluation, model quality, hallucination mitigation, guardrails, responsible AI, privacy, and security.
• Familiarity with AI/ML APIs, cloud platforms, vector databases, model providers, and frameworks such as LangChain or LlamaIndex.
• Strong analytical skills with experience using SQL, product analytics, A/B testing, experimentation, and product KPIs.
• Ability to define and measure AI product success metrics, including quality, accuracy, adoption, engagement, latency, cost, and ROI.
• Strong customer-centric mindset with experience in user research, customer discovery, competitive analysis, and market assessment.
• Demonstrated ability to make data-driven product decisions in ambiguous and rapidly evolving technology environments.
• Strong stakeholder management, communication, storytelling, negotiation, and executive-presentation skills.
• Experience with AI product commercialization, pricing, partnerships, or go-to-market strategy is an advantage.
• Technical proficiency in Python, APIs, SQL, or AI/ML tooling is desirable but not necessarily mandatory.
• Bachelors degree in Computer Science, Engineering, AI/ML, Data Science, Business, or a related field; an MBA or advanced technical degree is an advantage.