Senior Engineer, Data and Wealth AI Platform | CTC Upto - 30-35LPA

Senior Engineer, Data and Wealth AI Platform | Kotak Securities

Location: Mumbai

Employment: Full-time, permanent

Experience: 3–7 years

Company Description

Kotak Securities is a subsidiary of Kotak Mahindra Bank. The group was founded in 1985 and was the first NBFC in India to convert into a commercial bank. It is now building the data and AI services behind Kotak Neo, its wealth platform. The roadmap is funded from operating earnings on a multi-year horizon. The team works under SEBI, RBI and DPDPA oversight, so auditability and explainability are built in from day one.

Role Description

You'll build the intelligence layer of Kotak's wealth business. That means one unified view of every investor and partner, and the AI that turns it into action.

You'll design FastAPI services that compute investor profiles, scores and signals from the data lake. These are exposed as versioned APIs to the Node.js and React teams. You'll also build the pipelines behind them, covering RTA feeds, transactions, Account Aggregator and MF Central data, with quality checks and lineage throughout.

On the AI side, you'll ship LLM features end to end, such as document retrieval, PDF and statement extraction, and structured outputs. Each comes with proper evaluation and cost budgets. Where classic models fit better, you'll build those too, including propensity, churn and anomaly detection.

You own what you ship, from API contracts to on-call. Node.js engineers strong on data and keen to move to Python are welcome.

Qualifications

• 3–7 years of production software experience, including 2+ years building Python backend services used by real users.
• Strong Python skills:
• async, typing and pytest
• FastAPI or similar
• clean, versioned REST APIs
• Solid SQL and data modelling, plus pandas, Polars or PySpark on large datasets.
• At least one LLM feature shipped to production, and the ability to explain how you evaluated it, not just how you prompted it.
• Comfort with a cloud data stack:
• object storage
• a lakehouse or warehouse (Delta, Iceberg, Snowflake, BigQuery or Redshift)
• Airflow or a similar scheduler
• Docker, CI/CD and observability basics.
• Enough TypeScript and Node.js to integrate with existing services.

Bonus:

• Indian wealth or broking domain knowledge (mutual funds, CAMS/KFintech, Account Aggregator, CAS)
• Kafka
• Vector stores
• Regulated-environment experience
• Open-source work