About the Role

We are a Non-Banking Financial Company (NBFC) offering digital vehicle loans, with most of our customer journey delivered through our mobile application. Our product spans the full lending lifecycle application, underwriting, disbursal, servicing, and collections.

We are modernising these journeys by embedding artificial intelligence across key stages of the lifecycle, with the goal of reducing manual effort, improving turnaround time, and strengthening decision quality. This role will own a defined segment of that transformation.

The successful candidate will operate as a hands-on product owner: working directly with data, partnering closely with operations and credit teams, and making informed decisions about where automation adds value and where human judgment must remain. This is a high-ownership role suited to a candidate who is comfortable operating with autonomy in a lean, fast-moving environment.

Key Responsibilities

- Own one or more lending journeys end to end (for example, customer onboarding and document verification, or servicing and collections), from problem definition through delivery and post-launch performance.
- Manage core lending technology lifecycle through SaaS vendors.
- Assess where AI and automation deliver genuine value across the lending lifecycle, and where they are not the appropriate solution.
- Define clear, measurable success criteria for each initiative such as straight-through-processing rate, turnaround time, cost per application, and error thresholds and hold delivery accountable to them.




- Design human-in-the-loop workflows that determine how the system behaves under uncertainty, including review pathways, service levels, and associated operational cost.
- Partner cross-functionally with Credit, Risk, Operations, Legal, and Compliance to bring initiatives to production within a regulated environment.
- Monitor live product performance, including model drift, edge cases, and adoption, and drive continuous improvement based on operational data.

Required Qualifications

- Demonstrated product management experience in lending, credit, or financial services, with working knowledge of core lending concepts (e.g. DPD buckets, NACH mandates, LOS and LMS systems, and the constraints under which credit teams operate).
- Experience delivering products within a regulated environment, including direct engagement with compliance and legal stakeholders.
- Proficiency in reading and interrogating data independently using SQL or a business intelligence tool, without reliance on analyst support for routine questions.

AI Competency This role requires informed oversight of AI initiatives rather than hands-on model development. The successful candidate should be able to:

- Identify where large language models or machine learning are the appropriate tool, and where they are not.




- Understand common failure modes, including model uncertainty, confidently incorrect outputs, and the operational limits of high-accuracy models.
- Draw on any prior experience scoping, evaluating, or delivering AI-enabled features such as document extraction, conversational interfaces, scoring, or triage including a candid account of outcomes and lessons learned.

Ways of Working The successful candidate will demonstrate:

- A first-hand approach to understanding operational reality, gained through direct engagement with operations teams and customers rather than dashboards alone.
- Explicit, concise written communication.
- Sound, self-critical judgment and a willingness to challenge their own assumptions.

What We Offer

- End-to-end ownership of product journeys that reach real customers.
- Direct access to senior product decision-making and clear visibility of business context.
- Meaningful exposure to how a regulated financial services business operates.
- A high degree of autonomy and influence within a small, capable team.

Application Process Candidates are requested to submit a CV together with brief written responses (a few paragraphs each) to the following:

1. Identify a lending journey you have worked on. What was the single largest source of manual effort, and how would you have addressed it with greater resources?
2. Where within a lending business would you decline to allow AI to make an autonomous decision, and why?

These responses are reviewed ahead of the CV and form a key part of our assessment.

📌 Assistant Product Manager (Bengaluru)
🏢 evfin
📍 Bengaluru