Senior Product Manager || Generative AI

Job Title: Senior Product Manager – Generative AI Location: Bangalore/Gurgaon Department: Product Reports To: Product Leader
About the Role We are looking for a dynamic and experienced Senior Product Manager – Generative AI to lead the strategy, development, and implementation of AI-driven products that transform customer and merchant experiences across our payments ecosystem. You will work closely with engineering, data science, compliance, and business teams to develop next-generation solutions powered by large language models (LLMs) and other generative AI technologies.
Key Responsibilities • Define and drive the roadmap for generative AI capabilities across our product suite (e.g., fraud detection, customer support automation, personalized payment experiences). • Work cross-functionally with AI/ML engineers, data scientists, UX designers, and business stakeholders to build, launch, and iterate on AI-powered features. • Identify customer pain points and develop AI-first product solutions that improve efficiency, security, and user engagement. • Evaluate third-party LLM platforms (e.g., OpenAI, Anthropic, Google) and work with internal teams to integrate them securely and effectively. • Monitor product performance using data and feedback, and use insights to optimize AI models and user interactions. • Ensure all AI product developments comply with financial regulations and data privacy laws (e.g., RBI, GDPR).

Required Qualifications • 4+ years of product management experience, with at least 1+ years in AI products; experience in payments or fintech is highly preferred. • Understanding of generative AI models (LLMs, transformers, embeddings) and their applications in real-world products. • Proven track record of shipping B2C or B2B AI/ML-driven products at scale. • Strong analytical, strategic thinking, and communication skills. • Ability to work in a fast-paced, cross-functional environment with regulatory sensitivity.

Nice to Have • Experience with prompt engineering and fine-tuning LLMs. • Background in data science, machine learning, or software engineering. • Familiarity with payment ecosystems, risk modeling, and fraud analytics.