How do I apply for AI Product Manager at LambdaTest?

You can view the full description and apply for AI Product Manager at LambdaTest on EchoJobs: https://echojobs.io/job/lambdatest-ai-product-manager-nd2wh.

LambdaTest is hiring a AI Product Manager — a full-time, based in Noida, India role. Apply directly on LambdaTest's careers page below.

AI PRODUCT MANAGER

Location: Noida, India

Department: Engineering

Experience: 2 to 4 years

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

🚀 AI-Native Product Ownership (50%)

Own a product surface from discovery through production deployment — roughly 80% of the SDLC — and stay accountable until it is in a customer's hands.
Ship 13 new AI integrations in your first six months, designing LLM-powered workflows that remove manual steps from the quality engineering lifecycle.
Build and integrate agents into the existing platform, including MCP creation. Prototype with Claude and other LLMs directly, rather than specifying prototypes for someone else to build.

⚙️ Execution and Operational Excellence (30%)

Run sprint planning, clear roadblocks with engineering, manage technical debt honestly, and hold a high shipping cadence.
Use product analytics to identify user drop-offs and improve the overall product experience.
Keep roadmap, sprints and priorities transparent to everyone who depends on them, from engineering to sales.

🧠 Strategic Growth and Discovery (20%)

Build the roadmap for your surface from scratch. Treat it as your own company, not a queue handed down to you.
Run deep user interviews and feedback loops with quality engineering teams. Turn what you hear into shipped changes.
Spend roughly 30% of your time customer-facing — articulating why TestMu wins and building the documentation and collateral that carries that argument. No demos required.

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 agented.

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.

AI Product Manager

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