Position: AI Product Manager
Department: AI Division
Experience: 4-8 Years
Location: Onsite (Ahmedabad)
About the Role:
We are seeking an AI Product Manager who can lead the development of GenAI-powered products, internal AI tools, automation platforms, and client-facing AI solutions.
This role is ideal for someone who understands how modern AI products are built using LLMs, agents, automation workflows, APIs, data sources, and secure system design. The person should be able to convert business problems into clear AI product requirements, work closely with engineering teams, and ensure products are practical, secure, scalable, and valuable for end users.
As an AI Product Manager, you will bridge the gap between business needs, client expectations, and technical execution. You will work with AI Engineers, Automation Engineers, Designers, and stakeholders to define product strategy, create clear requirements, manage delivery, and ensure strong product outcomes.
Key Responsibilities:
Product Strategy & Vision
-
Define and own the product vision, roadmap, and strategic direction for AI-powered products.
-
Translate business goals into clear AI product initiatives.
-
Identify business problems, manual workflows, and operational gaps that can be solved using GenAI, automation, and intelligent assistants.
-
Prioritize product ideas based on business value, feasibility, user impact, security, and scalability.
GenAI Product Development
-
Work closely with AI Engineers and Automation Engineers to design, build, and launch GenAI-based products.
-
Define product requirements for AI assistants, workflow automation, document intelligence, chat interfaces, knowledge systems, and agent-based solutions.
-
Collaborate with technical teams on LLM selection, prompt workflows, RAG-based systems, APIs, integrations, and data flows.
-
Define success metrics such as accuracy, response quality, latency, reliability, user adoption, cost, and business impact.
-
Review AI outputs and help define acceptance criteria for quality, safety, and usability.
Security, Governance & Responsible AI
-
Ensure AI products follow proper security, privacy, and data-handling practices.
-
Work with teams to define guardrails for sensitive data, client data, access control, and user permissions.
-
Help evaluate risks related to hallucination, incorrect outputs, data leakage, prompt injection, and misuse of AI systems.
-
Ensure AI features include proper human review, fallback handling, auditability, and responsible AI principles where required.
-
Collaborate with engineering teams to design secure workflows for third-party tools, APIs, cloud platforms, and LLM providers.
Technical Product Leadership
-
Participate in technical discussions with engineering teams and challenge assumptions where needed.
-
Understand the practical implementation of GenAI products, including prompts, embeddings, vector databases, APIs, integrations, and automation workflows.
-
Act as the bridge between technical teams, business stakeholders, and clients.
-
Convert complex technical topics into simple explanations for non-technical stakeholders.
Agile Product Delivery
-
Own backlog prioritization, sprint planning, roadmap execution, and Agile ceremonies.
-
Create clear PRDs, user stories, acceptance criteria, release plans, and product documentation.
-
Ensure timely delivery of features while maintaining product quality, security, and business alignment.
-
Coordinate with design, development, QA, and client-facing teams to move products from idea to launch.
Stakeholder Management
-
Work directly with clients, business leaders, and internal teams to gather requirements and define product goals.
-
Present product updates, roadmap plans, demos, progress reports, and performance insights.
-
Manage expectations around AI capabilities, limitations, timelines, and risks.
-
Support discovery calls, requirement workshops, and product demos when needed.
Data-Driven Decision Making
-
Define KPIs and success metrics for AI products.
-
Analyze user feedback, product usage, AI response quality, and business outcomes.
-
Use data and feedback to improve AI workflows, prompts, product experience, and feature prioritization.
-
Drive continuous improvement after launch.
Required Skills & Qualifications:
Experience
-
4–8 years of total experience.
-
2+ years of hands-on AI/ML Engineering or AI Software Development experience.
-
2+ years of Product Management experience in an Agile environment.
-
Experience working on AI, GenAI, SaaS, automation, or technology products.
-
Prior experience working closely with AI/engineering teams is required.
GenAI & Technical Understanding
Strong understanding of:
-
Generative AI and Large Language Models.
-
AI agents and workflow automation.
-
Prompt engineering and prompt evaluation.
-
RAG-based systems and knowledge bases.
-
APIs, webhooks, integrations, and data flows.
-
Vector databases and embeddings at a conceptual/product level.
-
AI quality evaluation, hallucination control, and human-in-the-loop workflows.
-
Basic cloud and deployment concepts.
-
Security, privacy, access control, and data governance for AI products.
Product Management Skills
-
Strong experience with Agile/Scrum methodologies.
-
Ability to write detailed PRDs, user stories, acceptance criteria, and product documentation.
-
Experience managing product roadmaps and end-to-end product lifecycle.
-
Ability to balance business priorities, technical feasibility, user experience, cost, and security.
-
Strong problem-solving and prioritization skills.
Communication & Leadership
-
Excellent stakeholder management and client-facing communication skills.
-
Ability to explain AI concepts clearly to non-technical users.
-
Strong analytical thinking and structured decision-making.
-
Ability to influence cross-functional teams without direct authority.
-
Comfortable working with engineering, design, QA, leadership, and client teams.
Tools
-
Jira, Confluence, Figma, Notion, Postman, SQL
-
ChatGPT / Claude / Gemini or similar GenAI tools
-
Basic understanding of automation tools such as n8n, Zapier, Make, or similar platforms is a plus
Education
-
Bachelor's degree in Computer Science, Engineering, Information Technology, Artificial Intelligence, or a related field.
-
MBA or Product Management certification is a plus.
Preferred Qualifications
-
Experience building or managing GenAI products in production.
-
Exposure to OpenAI, Anthropic, Gemini, Claude, OpenRouter, or similar LLM ecosystems.
-
Experience working on AI assistants, automation tools, internal productivity tools, or SaaS platforms.
-
Understanding of AI governance, responsible AI, security reviews, and data privacy.
-
Experience with cloud platforms such as AWS, Azure, or GCP.
-
Experience working in B2B, SaaS, agency, or AI-first product environments.
-
Ability to evaluate AI product risks such as hallucination, data exposure, unreliable outputs, and user trust issues.
