Description :

Location : Bangalore / Mumbai

Role CTO

Type : Full-time

Experience : 5 - 10 years (AI/ML leadership).

Reports to : Founder / CEO

Industry : AI, Fintech, Consumer internet

Equity - 2 - 7 % (based on discussion)

About Founder : Harshvardhan Lunia is one of Indias most respected thought leaders in the fintech space and founder of Lendingkart. The platform has disbursed an estimated 20,000 crore+ and 14500+ pincodes reporting with one of the highest profit margins in the digital lending industry. The company also built one of the most advanced co-lending partnerships framework for MSMEs with 20+ banks and financial institutions and transformed credit access for millions of MSMEs across India. Under his leadership, Lendingkart became one of the most successful digital lending fintechs of the past decade.

He has been bestowed with prestigious awards presented by the Finance Minister, Ms. Nirmala Sitharaman, including Best Fintech, and has been featured by Forbes magazine. The company has also received multiple industry recognitions such as Best Fintech in Lending (BFSI, ET), Best Place to Work, and Dream Company to Work, among others.

Ask Birbal - AI concierge for Financial services :

We plan to create an AI Financial concierge that guides users from what should I do? to its done across financial services. We plan to start with Loan products creating a platform that helps in discovery, delivery and long term customer support for them. Finally helping the customer to manage all his loans and account liabilities at one place.

Problem :

Financial decisions in India are high-stakes and messy:

Users face anxiety, confusion, and decision paralysis during product selection.

After choosing, execution is fragmented across banks, DSAs, KYC, vendors, and follow-ups.

Post-disbursal support is inconsistent and slowhurting trust and sometimes credit scores.

Existing tools answer questions, but dont guarantee correctness, continuity, and dont drive outcomes to closure.

Solution :

We will replace forms, intermediaries and disconnected touchpoints with executed outcomes and full information for the consumer.

We will create ;

Conversational Intelligence : Natural, human-like guidance that simplifies complex financial questions and gives instant, trusted answers.

AI-Powered Decision Support : Help compare, choose, and act on the best products without bias or confusion

Smart Personalization : Context-aware insights tailored to each users goals and financial needs.

Guided full delivery journey support : Beginning from Application process, document management, periodic updates, query resolutions, sanctions and disbursals.

Problem Resolution: Continuous support across the entire lifecycle of financial products/services to resolve issues faster and with less effort.

Key Responsibilities :

1. AI-First Product & Architecture

- Design systems where AI/ML is embedded into core workflows

- Decide what should be automated, augmented, or human-in-loop

- Own model selection: build vs fine-tune vs API usage

- Architect scalable, modular, and secure AI systems

2. Data & ML Ownership

- Define data strategy: ingestion, labeling, quality, feedback loops

- Build and maintain ML pipelines (training, evaluation, deployment)

- Implement monitoring for drift, bias, accuracy, and cost

- Ensure explainability and auditability where required

3. Engineering Leadership

- Hire, mentor, and lead a high-caliber engineering team

- Set coding standards, review culture, and release discipline

- Balance speed vs reliability in an early-stage environment

- Own infra decisions (cloud, CI/CD, observability)

4. Security, Compliance & Reliability

- Own data security and access controls

- Ensure compliance (especially for fintech / regulated domains)

- Design systems with audit trails and reversibility

- Maintain high uptime and graceful failure handling

5. Founder & Business Partner

- Work closely with founder on roadmap and trade-offs

- Translate business problems into technical solutions

- Communicate clearly with non-technical stakeholders

- Represent tech credibility with investors and partners

Must-Have Skills & Experience :

Technical

- Strong backend engineering background (Python / Java / Go / Node)

- Hands-on experience with:

LLMs (OpenAI / Anthropic / open-source)

Prompting, RAG, fine-tuning

ML frameworks (PyTorch / TensorFlow)

Experience deploying ML systems in production

Cloud infrastructure (AWS / GCP / Azure)

AI-Native Mindset

- Thinks in workflows, agents, and automation

- Knows limitations of models and how to design around them

- Cost-aware AI design (latency, inference cost, scale)

- Comfortable iterating fast with imperfect models

Leadership

- Has built and scaled teams (5 30+ engineers is ideal)

- Can attract strong engineers

- Clear decision-maker under ambiguity

Nice to Have :

- Fintech / lending / regulated industry experience

- Experience with:

Vector databases

Real-time decisioning systems

Workflow orchestration (Temporal, Airflow, etc.)

Open-source contributions or technical writing

Startup experience (01 or 110)

What Success Looks Like (1218 months) :

- Core product is AI-driven, stable, and scalable

- Clear data flywheel in place

- Engineering velocity is high with low tech debt

- Team can ship without constant firefighting

- Tech is a competitive moat, not a cost center

Why Join :

- Real ownership and decision power

- Build category-defining AI systems

- Direct impact on product, customers, and revenue

- Long-term upside (equity meaningful, not decorative)