About the Role:

We are hiring a Product Owner (AI-First) to lead the next wave of innovation across our lending platforms.

This is not a traditional product role - we are looking for someone who treats AI as a first-class capability, not a feature, and who can rethink legacy NBFC workflows from the ground up using data, GenAI and agentic systems, while remaining grounded in feasibility, risk and unit economics.

The role spans four product surfaces:

- Vehicle finance - used and new commercial vehicles, cars and refinance journeys.

- MSME and business loans - secured SME lending workflows.

- Loan origination and underwriting platforms - sourcing, KYC, credit decisioning and disbursal.

- Collections and customer servicing - post-disbursement journeys, recovery, helpdesk and self-service.

You will partner with engineering, design, data science, credit, risk, compliance and business teams to ship products that materially move TAT, conversion, credit quality, customer experience and cost-to-serve.

Key Responsibilities:

Product Strategy & AI-First Vision:

- Define and own the product vision and roadmap for assigned lending journeys, with a clear point of view on where AI/ML, GenAI and agentic workflows create durable value.

- Continuously scan the NBFC, BFSI and AI landscape - Account Aggregator framework, ULI, embedded finance, alternate data, LLMs, voice agents - and translate signals into product bets.

- Identify friction in current journeys (login-to-disbursal, underwriting, collections, servicing) and design AI-led solutions that reduce TAT, improve credit decisioning and lift collection efficiency.

Product Development & AI Delivery:

- Own the end-to-end product lifecycle - discovery, requirement gathering, sprint planning, release and iteration - for digital and AI-enabled features.

- Write crisp PRDs, user stories and acceptance criteria; where useful, build clickable prototypes or low-code/no-code mocks using modern AI tooling and prompt-based prototyping.

- Partner with data science to scope and ship ML / AI use cases such as alternate-data credit scoring, early-warning signals, propensity and next-best-action models, document AI for KYC and income proofs, GenAI copilots for relationship managers, and voice/chat agents for collections and servicing.

- Define guardrails for every AI feature - accuracy thresholds, human-in-the-loop checkpoints, fallback flows, override paths, model monitoring and rollback criteria.

Stakeholder Management:

- Act as the connective tissue between business (sales, credit, collections, customer service), technology, data science, design, risk and compliance.

- Run structured rituals - backlog grooming, sprint reviews, UAT, business demos - and maintain a single source of truth on priorities and trade-offs.

- Negotiate scope and sequencing with senior stakeholders using data, customer insight and clear hypotheses.

Product Performance & Experimentation:

- Define and track north-star and input metrics for each product area (e.g., login-to-disbursal TAT, approval rate, first-EMI default, collection efficiency, NPS, cost-to-serve, automation rate).

- Build a strong experimentation culture - A/B tests, champion-challenger models and structured pilots - before scaling features.

- Use analytics, BI and AI-assisted analysis to extract insights from large data sets and operational logs, and feed them back into the next iteration.

Responsible AI, Risk & Regulatory Compliance:

- Ensure all products comply with applicable Indian regulations and guidelines - RBI Master Directions for NBFCs, RBI Digital Lending Guidelines, KYC/AML norms, the DPDP Act 2023, and emerging guidance on responsible AI in financial services.

- Partner with risk, legal and compliance teams to design products that are fair, explainable, auditable and safe - especially for AI/ML-driven decisioning.

- Champion privacy-by-design and security-by-design: minimize data collection, protect sensitive customer information (PAN, Aadhaar, account and contact details) and never bypass approval or control mechanisms.

Qualifications & Requirements:

Experience:

- 4 - 6 years of experience as a Product Manager, Product Owner or in a related product role; experience in NBFC, banking, fintech or financial services strongly preferred.

- Demonstrated track record of shipping digital products in lending, onboarding, underwriting, collections or customer servicing - ideally with measurable business impact.

- Hands-on exposure to at least one AI/ML or GenAI-enabled product is a strong plus (e.g., LLM-powered assistants, document AI, chatbots/voicebots, ML-based scoring or fraud detection).

Technical & AI Fluency:

- Comfortable working with APIs, data pipelines and integrations across the lending stack (LOS/LMS, bureau, Account Aggregator, eKYC, eSign, payment rails) and modern cloud-based product environments.

- Strong working knowledge of how AI/ML and GenAI systems behave - strengths, failure modes, evaluation, hallucination control, prompt design, retrieval and human-in-the-loop design.

- Active, daily user of AI tools for product work - using GenAI to accelerate research, PRD writing, data analysis, mock generation, competitor scans and stakeholder communication.

- Data-driven mindset: comfortable with SQL or BI tools, basic statistical reasoning and reading model-performance metrics.

Mindset & Soft Skills:

- Out-of-the-box thinker - willing to challenge legacy NBFC workflows and propose AI-native alternatives, while staying grounded in feasibility, risk and unit economics.

- Strong customer empathy, especially for semi-urban and Bharat customer segments and frontline field teams.

- Excellent written and verbal communication; can translate between business, technology, data science and compliance audiences.

- Bias for action, ownership and outcomes; comfortable operating with ambiguity in a fast-moving environment.

Education:

- Bachelor's degree in Engineering, Computer Science, Business, Finance or a related field. MBA, PGDM or a specialization in product, analytics or AI is a plus.

What You Will Get:

- A real opportunity to shape AI-led lending at scale across vehicle finance, MSME, origination and collections.

- Direct exposure to senior leadership and cross-functional partners across credit, risk, business and technology.

- A culture that values speed, ownership, customer-first thinking and responsible use of technology and data.