Description: Product Manager AI / Senior Product Manager AI

Experience:

- 4 to 5 years overall Product Management experience

- Minimum 12 to 18 months working on AI or GenAI products

- Location: Mumbai, India

- Full-time | Work from Office

Role Overview:

We are hiring a Product Manager who has built and shipped AI-powered products in production.

This role owns AI-led initiatives across risk assessment, intelligence, user experience, operations, and internal tooling. AI is a core system for us, not a feature add-on.

You will work closely with founders, AI engineers, backend teams, and design to build meaningful, high-impact AI products.

What you will work on:

- Building and scaling our Risk Engine for risk assessment, scoring, and compliance decisions

- AI-driven data analytics across policies, claims, user behavior, and operations

- Converting messy insurance documents into structured, usable data

- Building systems that explain insurance policies in simple, human language

- Detecting coverage gaps, risks, exclusions, and anomalies automatically

- Voice intelligence including voice bots, call analysis, sentiment detection, and agent assist

- AI-assisted coding and internal tools to accelerate product development

- Designing AI-first product experiences in collaboration with design and engineering

- Applying GenAI, ML, and rule-based systems across the product lifecycle

- Owning accuracy, explainability, evaluation metrics, and guardrails for AI features

What we are looking for:

- Strong product fundamentals with end-to-end ownership mindset

- Hands-on experience shipping AI or GenAI features into production

- Ability to clearly define AI use cases, constraints, and success metrics

- Comfort working deeply with AI engineers and data teams

- Clear communication and structured thinking

What we expect from you (Very clear):

You must have:

- 4 to 5 years of Product Management experience

- 12 to 18 months of real, hands-on AI product work

- Experience working closely with AI engineers or data teams

- Shipped AI features into production, not just POCs

You should know

- Difference between LLMs, ML models, and rule-based systems

- Prompt design, hallucination risks, and AI limitations

- How to design fallbacks when AI systems fail

- Why AI UX is different from traditional product UX

What will make you stand out:

- Experience building decision engines, risk systems, or intelligence layers

- Prior work in consumer tech, fintech, or regulated domains

- Strong judgment on when not to use AI

What we are NOT looking for (Read carefully):

- PMs who only used ChatGPT for writing PRDs

- PMs who think AI equals OpenAI API integration

- PMs who avoid data, logic, or system design discussions

- PMs who wait for engineers to define solutions

If you have only managed AI vendors without understanding internals, this role will be painful.

Why join us:

- Work on real AI problems with real user impact

- High ownership, low bureaucracy environment

- Direct collaboration with founders

- Opportunity to shape AI as a core product capability