AI - Product Manager

Job description

**Role Overview** Lending, commerce, and advisory for millions of farmers, and you get to put AI at the center of it. As DeHaat's AI Product Manager, you'll own AI-powered features end-to-end across our B2B and B2C platforms, from farmer-facing assistants to the workflows that run our retail and lending business. You'll write the specs, build shoulder-to-shoulder with engineering using Claude, sit across the table from farmers and retailers to learn what actually matters, and let data, not opinions, decide what ships next. **Key Responsibilities** • Own AI-powered features end-to-end, from first insight to shipped product, across DeHaat's B2B/B2C platforms • Author precise, engineering-ready documentation, PRDs, product specs, user stories, and acceptance criteria for AI capabilities (assistants, recommendation engines, workflow automation), clear enough that engineering can build without guesswork • Build shoulder-to-shoulder with engineering to design, ship, and iterate on AI products powered by LLMs such as Claude • Get out of the building, talk to farmers, retailers, and business customers, and turn what you hear directly into product decisions • Define success metrics, run experiments and A/B tests, and let data be the loudest voice in the room • Keep a clean paper trail of product decisions and trade-offs, and collaborate closely with leadership, design, data science, and engineering across the full build cycle **Requirements & Qualifications** • 2-4 years of product management experience, ideally in B2B/B2C environments • Demonstrated hands-on experience building and shipping AI-powered products using LLMs (Claude or similar) • Solid grounding in user research methods and research science • A self-starter with a strong bias for execution, you'd rather ship and iterate than wait for the perfect plan • Excellent written and verbal communication; comfortable working directly and rapidly with engineers • Bachelor's/MBA from a Tier-I college. **Good to Have** • Experience in agritech, fintech, or lending-adjacent products, with hands-on experience solving real business problems using AI/LLMs, including prompt engineering and evaluation of LLM-based features.