The Role
Own an AI-native quality engineering product surface end to end, from discovery and roadmap development through deployment, adoption, and continuous improvement. Build LLM-powered workflows and agents using Claude and MCPs, drive sprint planning and execution, analyze product usage, conduct customer research, and coordinate with engineering, sales, and leadership. The role requires strong SaaS product experience, daily hands-on AI usage, clear communication, and full accountability for product outcomes.
Summary Generated by Built In
AI Product Manager
Product · Agentic Quality Engineering
📍 Noida · WFO 🕐 Full-Time · 2–4 Years
THE MISSION
We aren't automating scripts. We are deprecating the era of manual-heavy testing entirely. TestMu AI is building the world's first AI-native platform where Agentic Intelligence autonomously plans, authors, and self-heals the entire Quality Engineering lifecycle.
We are shifting from building tools to training agents. The name "TestMu" comes from our community conference our users and our team are the heartbeat of what we build, not an audience. And while we build AI, we build it as a partner: AI augments human potential, it does not replace it.
This role sits at the centre of that shift. You will own a product surface end to end and rebuild how product management itself gets done here — using agents.
THE PILLARS OF IMPACT
- Own a product surface end-to-end from discovery and solution design to production deployment and customer adoption.
- Build LLM-powered workflows that eliminate manual effort across the quality engineering lifecycle.
- Build and integrate AI agents into the existing platform, including MCPs, and prototype directly with Claude and other LLMs.
- Take ownership of product outcomes, not just requirements from defining the problem to shipping and improving the solution.
- Drive sprint planning, remove engineering roadblocks, manage technical debt, and maintain a strong shipping cadence.
- Use product analytics to identify user drop-offs, uncover friction, and improve the overall product experience.
- Keep the roadmap, priorities, and execution transparent across engineering, sales, and other stakeholders.
- Build and own the roadmap for your product surface from the ground up treating it like your own business, not a handed-down backlog.
- Conduct deep user interviews and build continuous feedback loops with quality engineering teams, turning insights into shipped product improvements.
- Stay close to customers, articulate why TestMu AI wins, and create the documentation and collateral that strengthens that story.
WHAT AI GIVES YOU
We have already removed around 60% of manual PM work here in the last six months across design, prototyping, and cognitive analysis. Our target is 80% fully agentic.
You get Claude and full LLM tooling access from day one, budget for whatever else you need, and explicit permission to automate your own job. Anything you agent away, you keep as leverage. Nobody here will ask you to do manually what a well-built agent can do at 2am.
You will also build agents into the product itself which means the thing you learn internally ships externally.
THE BAR
Signal: What you must prove
- Product depth. You have owned products end to end in a product role APM or PM, not an adjacent title.
- SaaS foundation. You have shipped in SaaS. B2B is where you will be most at home.
- AI in your hands, daily. You use LLMs as an operating system, not a feature. You can walk us through a workflow you built and shipped.
- Communication clarity. You will sit between engineering, sales, and customers. Clarity is not a soft skill in this role it is the job.
- Extreme Ownership: Takes full accountability for outcomes, not just tasks.
THE INTERVIEW LOOP · SCREENING FOR THE TOP 1%
Round: What happens
- Round I · Hiring Manager: Product discovery and the reasoning behind your prioritisation and roadmap decisions.
- Round II · Product Lead: AI and execution how you use LLMs today, and what you have built from zero.
- Round III · VP Engineering: Solving for scale technical debt, API and agent integration, communicating risk to stakeholders.
- Final · Leadership: Vision alignment. Readiness to lead the move from manual-heavy testing to agentic intelligence.
YOUR PATH
Product Manager → Senior Product Manager → Product Lead.
You move up when you own a surface end to end, lead sprint planning and customer calls, and hold product influence across a 5-10 person pod (influence, not headcount). Startup pace faster than the mid-size or enterprise equivalent.
Skills Required
- 2-4 years of product management experience
- End-to-end product ownership experience in an APM or Product Manager role
- Experience shipping SaaS products
- Hands-on daily use of LLMs, including building and shipping an AI workflow
- Experience building or integrating AI agents, MCPs, or LLM-powered workflows
- Strong product discovery, prioritization, and roadmap management skills
- Experience driving sprint planning and working with engineering teams
- Ability to communicate clearly with engineering, sales, customers, and leadership
- Extreme ownership and accountability for product outcomes
- B2B product experience
- Quality engineering or software testing domain experience
Am I A Good Fit?
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The Company
What We Do
LambdaTest, now TestMu AI, is an AI-native, agentic testing cloud for end-to-end software quality engineering. Its platform supports testing across web, mobile, and AI applications, helping organizations automate and improve software quality. The company develops tools for autonomous testing workflows and supports development teams seeking scalable quality-engineering capabilities across modern application environments.
