AI Product Manager / Technical Product Manager - GenAI

Job Title: AI Product Manager / Technical Product Manager - GenAI

Role Summary

We are looking for an AI Product Manager / Technical Product Manager with 6-8+ years of experience in product management, with strong experience delivering AI, Generative AI, or enterprise software products .

The ideal candidate will have hands-on exposure to LLMs such as Gemini and Claude , along with a strong understanding of Generative AI, Agentic AI, RAG, prompt engineering, and multi-agent architectures . Apple experience is preferred, and local candidates only .

Key Responsibilities

• Define and drive the product vision, strategy, roadmap, and priorities for AI-powered products.
• Translate business and customer needs into product requirements, user stories, and success metrics .
• Work closely with AI/ML engineers, software developers, architects, UX teams, and business stakeholders.
• Evaluate and compare LLMs such as Gemini, Claude, and other enterprise LLMs based on performance, cost, security, and business requirements.
• Define AI product requirements involving Generative AI, Agentic AI, RAG, prompt engineering, and multi-agent architectures .
• Identify and prioritize AI use cases that provide measurable business value.
• Partner with technical teams to design and deliver AI-powered enterprise solutions .
• Monitor product performance and use data-driven insights to improve AI products.
• Support AI model evaluation, testing, and continuous product improvement.
• Ensure AI products follow appropriate security, compliance, responsible AI, governance, and data privacy practices.
• Communicate product strategy, roadmap, progress, and business outcomes to stakeholders and executive leadership.
• Manage product delivery using Agile/Scrum methodologies and tools such as Jira or Azure DevOps.

Required Skills

Product Management

• 6-8+ years of Product Management experience
• Product strategy and roadmap development
• Requirements gathering and prioritization
• Product lifecycle management
• Success metrics and KPI definition
• Stakeholder and executive communication

AI / GenAI

• Generative AI
• Agentic AI
• RAG — Retrieval-Augmented Generation
• Prompt Engineering
• Multi-Agent Architectures
• Large Language Models (LLMs)
• Gemini
• Anthropic Claude
• Enterprise AI use cases

Technical / Platform Knowledge

• AI orchestration frameworks
• APIs
• Vector databases
• Enterprise AI platforms
• AI/ML application architecture
• Model evaluation and selection

Governance & Security

• Responsible AI
• AI governance
• Model evaluation
• Security and compliance
• Data privacy

Preferred Qualifications

• Apple experience preferred
• Experience developing AI products for enterprise customers
• Experience with AI orchestration frameworks and enterprise AI platforms
• Experience working with vector databases and AI APIs
• Experience in Agile/Scrum environments
• Experience with Jira, Azure DevOps , or similar tools
• Technical background in software development, AI/ML, cloud, or enterprise architecture is a strong advantage