AI Product Manager

GreyLabs; Bengaluru; Vor Ort; INR 4.000.000 - 7.000.000; Vollzeit

Zusammenfassung

GreyLabs AI builds enterprise-grade Voice AI systems for India's BFSI ecosystem. Our technology powers high-volume, regulated use cases across collections, sales, servicing, compliance, and customer engagement.

As an AI-first PM, you own end-to-end product from discovery to shipped product, collaborating with founders, engineering, and enterprise customers to shape product DNA and a durable moat.

Qualifikationen

• 3–6 years of product management experience in B2B SaaS or enterprise software.
• Shipped something meaningfully uses AI, with model behaviour and evaluation trade-offs.

Aufgaben

• Own end-to-end product function from discovery to shipped product.
• Work with founders, engineering, and enterprise customers to define AI agents handling real conversations.
• Define problems clearly and write precise, technically grounded specs with rationale.

Kenntnisse

AI product management

Technical fluency

Customer discovery

Roadmap ownership

Strong communicator

Tools

SQL basics

CRM tooling

Jobbeschreibung

What You'll Do

We are looking for an AI Product Manager who is as obsessed with outcomes as they are with the underlying technology. In this role, you won't just be managing a backlog. You will be defining the intelligence layer of voice-based AI agents operating in one of India's most complex, high-stakes industries: BFSI.

As an early member of a fast-paced startup, you will hold end-to-end ownership of the product function, from customer discovery to shipped product. You will work directly with founders, engineering, and enterprise customers to define how AI agents handle real conversations with real consequences, shaping both our product DNA and our competitive moat.

1. AI-First PM & Technical Fluency

• Build for AI: Architect product workflows where AI is the core engine, not a feature toggle. You'll define how enterprise operators configure, supervise, and trust autonomous voice agents, and how those agents recover gracefully when they fail.
• Build with AI: Leverage AI tools to accelerate discovery, sharpen specs, and evaluate product quality. In an AI-native company, the gap between product thinking and development is shrinking.
• Technical literacy: You have a working understanding of how voice AI stacks are assembled (ASR, NLP, TTS, dialogue management) and can engage credibly with engineers on latency, accuracy, and evaluation trade-offs. You're not expected to train models, but you must understand how they behave to make good product decisions.
• Customer proximity: Spend time embedded with operators at banks, NBFCs, and fintechs. Translate workflows, pain points, and regulatory constraints into crisp product opportunities, not feature lists.
• Problem-first thinking: Define problems clearly before prescribing solutions. Write precise, technically grounded specs that engineers can act on immediately, with a point of view on the why, not just the what.
• Roadmap ownership: Prioritize ruthlessly across a roadmap that balances short-term enterprise asks with long-term platform bets. Own the sequencing, the trade-offs, and the explanation to stakeholders when you say no.
• Ship: Manage sprint rhythms, remove blockers, and deliver. You own the outcome, not just the spec. Partner with sales and customer success to ensure new capabilities land, get adopted, and drive measurable results.

3. Product Craft & Judgment

As AI makes feature generation a commodity, knowing what to build, and the discipline to kill everything else, becomes the ultimate differentiator.

• Strong opinions, clearly argued: You have a point of view on what makes a great product and you can defend it with logic, not just data. You're not a requirements aggregator; you're an advocate for the right solution. You can walk into a room, say "we shouldn't build this," and be taken seriously.
• The discipline of no: Great PMs are defined as much by what they kill as what they ship. You know how to decline a customer request that would hurt the platform, push back on a feature that optimises for the wrong metric, and resist the pull of urgency when it conflicts with strategy.
• Execution bar: You care deeply about whether the thing you shipped actually worked, not just whether it went live. You define what "good" looks like before a feature launches, and you hold the team (and yourself) to it.

4. Ambiguity & Growth

• We are operating on the frontier of Voice AI in regulated Indian BFSI. There is no playbook. You should be comfortable experimenting, honest about what you don't yet know, and disciplined about learning fast. The best candidate for this role is energised by that ambiguity, not unsettled by it.

What We're Looking For

• 3–6 years of product management experience: with a meaningful stint in B2B SaaS or enterprise software. You've owned a product end-to-end, not just contributed features to someone else's roadmap.
• Demonstrated AI work: You've shipped something that meaningfully uses AI, professionally or in a side project with real users. You can speak to model behaviour, evaluation trade-offs, and the gap between demo and production.
• Technical comfort: You can read a data schema, write a basic SQL query, and hold a credible conversation with an engineer, without needing to be one.
• BFSI or regulated industry experience is a strong plus: Not because we need jargon, but because we need someone who has felt what it means to ship in an environment where compliance, auditability, and downtime risk are real.
• Clear, direct communicator: You write and speak with precision. Customers demand clarity, engineers demand specificity, and stakeholders demand confidence. You can deliver all three.

Why Join Us?

GreyLabs AI builds enterprise-grade Voice AI systems for India's BFSI ecosystem. Our technology powers high-volume, regulated use cases across collections, sales, servicing, compliance, and customer engagement.

We work with 40+ leading banks, NBFCs, fintechs, and insurance companies, solving complex, real-world problems where performance, reliability, auditability, and data security are non-negotiable. Our systems operate at scale, handling millions of interactions across diverse languages, accents, and customer contexts.

As a Series A-funded company, we are scaling rapidly - deepening our product capabilities, expanding our enterprise footprint, and building long-term technology moats in AI-first workflows.

At GreyLabs, ownership is real. We value clarity of thinking, bias for action, intellectual honesty, and high craft standards. Teams operate with autonomy, move fast, and are trusted to take ideas from concept to production.

If you're excited about building meaningful technology in a high-impact, high-accountability environment, you'll feel at home here.