The Role

You will co-own AI products alongside the Head of Product. This is a building role, you'll own features end-to-end, ship them, measure their impact, and iterate based on real editorial feedback.

What your work will involve:

• Designing and running evaluations for AI features, proofreading accuracy, translation quality, summarization fidelity and using those results to drive product decisions.
• Shaping agent workflows as the platform moves from single-shot prompts to multi-step, tool-using agents. You'll think through orchestration, failure handling, and user experience together.
• Setting up and maintaining product analytics, building dashboards, running experiments, and producing intelligence reports that editorial leadership can act on.
• Working closely with engineers and designers in short, iterative cycles.
• Spending time with editorial users, understanding their workflows, identifying friction, and translating observations into product improvements.

What We're Looking For

2–4 years of product management experience. We value sharpness, curiosity, and follow-through over seniority.

You should bring:

• Hands-on experience with AI evaluations, you're familiar with concepts like precision, recall, human-in-the-loop eval, and building evaluation datasets. You've done this work, not just studied it.
• A working understanding of agent workflows, tool use, function calling, orchestration patterns, and how to design multi-step systems that handle edge cases well.
• Comfort with LLM integration patterns, including protocols like MCP (Model Context Protocol) and how tools connect to language models in practice.
• A solid analytics foundation you're comfortable writing SQL, working with analytics platforms, and building product metrics dashboards independently.

Strong signals we look for:

• You've shipped AI features in production environments, not just prototyped them.
• You've worked in small, fast-moving teams where you wore multiple hats and owned outcomes.
• You have informed opinions about model selection, RAG architectures, or evaluation frameworks and can articulate the reasoning behind them.
• You actively learn in public, through a blog, newsletter, community contributions, or a well-maintained knowledge base on AI tools and workflows.
• AI-native development tools (Claude Code, Cursor, or similar) are part of your daily routine, not something you've tried once.

Tools You'll Work With

• Jira, Figma, Slack, GitHub
• Google Analytics
• MySQL
• AWS Bedrock and LLM APIs
• Agent orchestration frameworks

Why This Role

• Ownership from day one. You'll follow a structured 30/60/90 onboarding plan, with clear ownership of a product line within your first quarter.
• Real AI work, real users. This isn't a proof-of-concept. Our AI product is live, integrated into the editorial CMS, and used by journalists producing content that hundreds of millions of people read. The feedback loop is immediate and the stakes are tangible.
• Small team, institutional reach. You'll work within a focused product and technology team inside India's largest media company, combining the pace of a building team with the scale and reach that few organisations can offer.
• Direct editorial exposure. You'll sit with editors and journalists, observe their workflows firsthand, and see the impact of what you build reflected in how news gets made every day