Job Purpose This is a single role combining product management and delivery management for Bajaj Finances Consumer AI programme which is building an AI-first way for customers to discover compare buy and service our lending savings insurance and consumer-durable financing products both on our app and web and inside frontier AI platforms such as ChatGPT Gemini and Claude. The jobholder owns outcomes for their pods features end to end deciding what to build and why then driving it through design engineering testing and release with internal teams and technology partners and improving it after launch based on data. The role sits in one of four pods (BLU Bots Agents Avatars or MCP) that share one platform and works across pods as priorities change. Duties and Responsibilities 1. Product Ownership & Roadmap (Core) Own the roadmap and backlog for the pods features prioritised by customer impact business value and MVP scope. Balance short-term delivery with the long-term direction of the shared Consumer AI platform. Track how banks fintechs and frontier AI platforms are changing consumer AI experiences and bring that into product decisions. 2. Requirements & Product Definition Turn customer needs journey data and business goals into problem statements PRDs user stories and acceptance criteria. Specify conversation flows intents and adaptive (fluid) UI behaviour using RICE or similar prioritisation. 3. Conversational & Multimodal Experience Design Work with design to create text voice image and avatar experiences that are consistent across pods. Validate flows and prototypes with customers early and iterate before build. 4. Delivery & Project Management Plan and run delivery: sprint planning release plans and dependency maps across pods platform teams and partners. Track scope timelines risks and issues (RAID); raise problems early with options and a recommendation. Coordinate UAT release readiness go-live and rollback plans with engineering QA and operations. Manage partner and vendor deliverables against agreed milestones and quality. 5.



AI Quality Risk & Compliance Define evaluation criteria and test scenarios; review AI quality (accuracy groundedness intent recognition) before every release. Ensure regulated content (rates fees Key Fact Statements consent and disclosures) always comes from systems of record and is never freely generated by the AI. Work with compliance risk legal and grievance teams as design partners applying RBI digital lending and responsible-AI expectations and the DPDP Act. 6. Stakeholder Management & Communication Act as the point of alignment between leadership business engineering design compliance and partners. Run delivery governance: status reporting and updates for leadership reviews. 7. Metrics Adoption & Continuous Improvement Define success metrics for every feature (completed journeys conversion against the app flow resolution without handoff repeat usage cost per resolved request). Use conversation analytics customer feedback and incidents to drive continuous improvement. 8. Pod Focus Areas (depending on the pod assigned) BLU Bots: multimodal chat the adaptive UI component library intent understanding and multilingual conversation (including Hinglish and vernacular). Agents: loan EMI card payment and servicing journeys carried out inside the conversation; action orchestration step-up authentication and audit trails. Avatars: voice and avatar experiences speech-to-text and text-to-speech quality response latency and vernacular voice. MCP: Bajaj discovery and read-only journeys on frontier AI platforms structured product and offer feeds handoff to Bajaj Key Decisions / Dimensions Feature prioritisation and backlog sequencing within the pods MVP scope. Go / No-Go recommendation for releases based on evaluation UAT and compliance sign-off.



Scope timeline and trade-off decisions; escalation of risks to the Pod Lead / Delivery Head. Acceptance of partner and vendor deliverables. Major Challenges Moving rapid on AI innovation while staying compliant in lending insurance and payments. Driving delivery across pods platform teams and external partners with shared dependencies. Keeping AI quality high (grounded answers no hallucinated rates or eligibility multilingual accuracy) at scale. Owning both product and delivery outcomes without trading one off against the other. Required Qualifications and Experience Educational Qualifications B.E. / in Computer Science Information Technology or related discipline. MBA from a recognised institution (preferred). Skills Hands-on experience of the Product and Software Development Life Cycles (PDLC / SDLC) in Agile / Scrum teams having run sprints and releases end to end. Ability to write PRDs user stories acceptance criteria and functional specs. Working understanding of LLMs and conversational AI (prompting retrieval-augmented generation intents evaluation and their limitations) enough to make trade-offs with engineers. Delivery management: release planning dependency and risk management (RAID) UAT and go-live. Data-driven decision-making: funnels A/B tests analytics tools or SQL. Excellent communication and stakeholder management across business engineering design and compliance. Nice to Have (But Not Mandatory) Experience in BFSI fintech lending payments or insurance products with awareness of KYC e-mandate KFS and consent journeys. Has shipped a chatbot voice assistant or generative-AI feature to production at scale. Exposure to Model Context Protocol (MCP) agent frameworks or ChatGPT / Gemini app ecosystems. Experience managing external vendors or system integrators. Familiarity with Jira Confluence Figma and analytics tools; CSPO / CSM / PMP certification is a plus. a)Work Experience 46 years in product management technical project or program management or a mix of both. At least 2 years delivering a customer-facing digital product (app or web). Required Experience: Senior IC

📌 Senior Ai Product Specialist (Pune)
🏢 Bajaj Finance
📍 Pune