AI Product Manager

Coxvi Technologies; Bengaluru; Hybrid; INR 2,500,000 - 4,500,000; Full time

Job summary

Coxvi Technologies in Bengaluru is seeking an AI-first Product Manager who can take a product problem from ambiguity to launch. You will research markets, talk to customers, prototype ideas, build AI agents, and own end-to-end launches.

The role requires hands-on experience building with LLMs and agents, deep product judgment, and the ability to work closely with engineering to ship ambitious AI-enabled workflows.

Qualifications

• 1 year hands-on experience building with LLMs, agents, or AI applications.
• Built actual AI workflows rather than only used ChatGPT or managed an AI project.
• Ability to simplify complex problems into product requirements.
• Comfort collaborating with engineers and understanding trade-offs.
• Experience with customer research and feedback loops.

Responsibilities

• Own AI-native workflows and agent experiences from concept to launch.
• Prototype AI agents using modern tools and evaluate outcomes.
• Define product strategy and align with engineering, design, and sales.
• Turn ambiguous ideas into actionable requirements and experiments.
• Measure adoption and iterate post-launch based on data.

Skills

Hands-on AI product building

LLMs and agents

Product strategy and market research

Customer discovery

Strong communication

Tools

Claude Code

Codex

OpenAI Agents SDK

LangGraph

Cursor

MCP

Langfuse

Job description

The Role We are looking for an AI-first Product Manager who can take a product problem from ambiguity to launch. This is not a traditional PM role where your primary responsibility is writing requirements and coordinating between teams.

You will be expected to research markets, talk to customers, identify opportunities, prototype ideas, build AI agents and evaluations, define product strategy, work closely with engineering, and own launches end-to-end.

We want someone who has spent meaningful time actually building with LLMs and agents, understands what these systems can and cannot reliably do, and can convert rapidly evolving AI capabilities into useful products.

What You'll Own

• Product Strategy & Discovery - Understand customers, workflows, pain points, and emerging opportunities.
• Conduct market and competitor research independently.
• Identify product bets and translate them into clear hypotheses.
• Decide what should be built now, later, or not at all.
• Develop a strong point of view on how AI changes existing workflows rather than simply adding an AI feature to them.

AI & Agentic Product Development

• Design AI-native workflows and agentic product experiences.
• Build prototypes and working agents yourself using modern AI tools.
• Experiment with prompts, models, tools, context, memory, workflows, and orchestration.
• Create datasets and evals to measure whether AI features actually work.
• Identify failure modes and work with engineering to improve reliability.
• Keep up with new models and capabilities and quickly test whether they create product opportunities.

Product Execution

• Turn ambiguous ideas into clear product requirements and workflows.
• Break large ideas into small experiments that can be shipped quickly.
• Communicate customer problems, edge cases, and product intent clearly to engineers and designers.
• Work closely with engineering throughout implementation rather than simply handing over a PRD.
• Test the product yourself and continuously improve it based on actual usage.

Customers & Market

• Speak directly with customers and prospects.
• Understand how they currently solve problems and where existing tools fail.
• Run product demos and gather structured feedback.
• Separate individual customer requests from broader product opportunities.
• Use customer conversations to continuously refine product strategy.

Launch & Growth

• Own launch strategy for the products and features you build.
• Define positioning, messaging, demos, onboarding, and initial adoption strategy.
• Work across product, engineering, sales, and customers to make launches successful.
• Measure what happened after launch and iterate quickly.

What We're Looking For You likely have 24 years of experience across product, engineering, startups, consulting, AI, or related roles. More importantly, you should have:

• ~1 year of hands-on experience building with LLMs, agents, or AI applications.
• Built actual AI workflows rather than only used ChatGPT or managed an AI project.
• Strong product judgment and ability to simplify complicated problems.
• Comfort working with engineers and understanding technical trade-offs.
• Ability to perform deep market and customer research independently.
• Strong written and verbal communication.
• High ownership — you naturally move from identifying a problem to getting something shipped.
• Comfort operating in an environment where the answer is often not known beforehand.

Two Traits We Care About Deeply

Constraint Thinking

Great product people don't start with: "What could we build?" They start with: "Given our users, technology, time, team, data, and constraints, what is the smartest thing we can build?" We value people who can reduce a large possibility space into a small number of high-leverage decisions. You should be able to distinguish between:

• interesting vs. useful
• possible vs. reliable
• demoable vs. production-ready
• customer requests vs. underlying problems
• AI capability vs. AI product

Grounded Energy AI moves incredibly fast, and it is easy to either become overly skeptical or overly excited. We want someone who has high energy without hype. You should be excited enough to constantly experiment with new technology, while grounded enough to recognize its limitations. You should naturally ask:

• Does this actually work?
• How often does it fail?
• What happens at scale?
• Can we evaluate it?
• Will customers actually change their behaviour for this?
• Is AI even necessary here?

You Might Be a Great Fit If You have independently done things like:

• Built an agent over a weekend to test a product idea.
• Compared multiple LLMs for a real use case.
• Created an eval dataset to test AI quality.
• Used tools such as Claude Code, Codex, Cursor, LangGraph, OpenAI Agents SDK, MCP, Langfuse, or similar systems.
• Automated parts of your own product or research workflow with agents.
• Interviewed users and changed the product based on what you learned.
• Gone from idea to prototype to customer feedback to production.
• Read product documentation, GitHub repos, Reddit discussions, research papers, and competitor products to understand a market deeply.

This Role Is Probably Not For You If

• You primarily see PM as backlog management and sprint coordination.
• You need detailed requirements before you can start working.
• You prefer delegating prototyping and experimentation entirely to engineering.
• You haven't spent meaningful time building with modern AI tools.
• You enjoy creating large strategy documents more than testing ideas with users.
• You are uncomfortable making decisions with incomplete information.

What Success Looks Like

Within your first few months, you should be able to independently:

• understand a customer problem
• research the market
• identify a promising product opportunity
• prototype an AI workflow
• define how its quality should be evaluated
• work with engineering to productionize it
• Speak with early users
• launch it
• measure adoption
• and recommend what we should do next

• Location:** Bangalore Hybrid / WFH with regular in-person collaboration
• Experience:** 24 years

Qualifications

• ~1 year of hands-on experience building with LLMs, agents, or AI applications
• Built actual AI workflows rather than only used ChatGPT or managed an AI project
• Strong product judgment and ability to simplify complicated problems
• Comfort working with engineers and understanding technical trade-offs
• Ability to perform deep market and customer research independently

SkillsGood to have

• Build and evaluate AI agents and workflows end-to-end
• Conduct independent market research and customer discovery
• Prototype AI products with hands-on LLM experimentation
• Define product strategy with constraint-based thinking
• Ship products from ambiguity to launch with high ownership