Senior AI Product Specialist

Job Purpose

This is a single role combining product management and delivery management for Bajaj Finance's 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 pod's 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.

• Own the roadmap and backlog for the pod's 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.

• 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.

• 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.

• 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.

• 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.

• Act as the point of alignment between leadership, business, engineering, design, compliance and partners.

• Run delivery governance: status reporting and updates for leadership reviews.

• 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.

• 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 pod's 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 fast 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. / B.Tech 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.

• 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

• 4–6 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).