Data Scientist - AI Engineer

Sagility; Bengaluru; On-site; INR 2,800,000 - 5,600,000; Full time

Job summary

Sagility is building AI-driven solutions on Databricks and Fabric platforms for US healthcare ops, including claims, payment integrity, care management and contact center. This hands-on role requires 7–12 years in data/software/analytics or ML, with at least 2 years building GenAI in production.

You will mentor BI/ETL engineers, deploy end-to-end GenAI, and ensure compliance with HIPAA/PHI while delivering measurable value across use cases.

Qualifications

• 7–12 years in data, software, analytics or ML engineering.
• At least 2 years building GenAI solutions live in production.
• Hands-on with Azure OpenAI, AI Foundry, Databricks or Fabric.
• Experience evaluating and monitoring LLM deployments in production.

Responsibilities

• Build GenAI and agent-based solutions end to end from design through deployment and monitoring.
• Deliver analytics use cases such as conversational analytics and text-to-SQL, document intelligence, automated insights and data-quality checks.
• Build RAG pipelines and vector search over Databricks, SharePoint and enterprise APIs.
• Set up evaluation (groundedness, hallucination, retrieval quality, regression) and monitoring for latency, tokens, cost, errors.
• Keep solutions compliant with HIPAA and PHI requirements, including masking and access-controlled retrieval.
• Work with operations leaders to find use cases worth building and prove their value.
• Mentor BI and ETL engineers and set up reusable standards for the team.

Skills

Python

SQL

Azure OpenAI

AI Foundry

Databricks

Fabric

RAG

Vector search

Agents

CI/CD

Azure deploy

Job description

To build AI solutions on our Databricks and Fabric platforms for US healthcare operations such as claims, payment integrity, care management and contact centre, and help our BI and ETL engineers grow into AI work. This is a hands‑on role.

Experience: 7 -12 years in data, software or analytics or ML engineering, with at least 2 years building GenAI solutions that are live in production

What you'll do

• Build and run GenAI and agent-based solutions end to end, from design through deployment and monitoring, using Azure OpenAI, AI Foundry and Databricks Mosaic AI.
• Deliver analytics use cases such as conversational analytics and text-to-SQL, document intelligence, automated insights and data-quality checks.
• Build RAG pipelines and vector search over Databricks, SharePoint and enterprise APIs.
• Set up evaluation (groundedness, hallucination, retrieval quality, regression) and monitoring (latency, tokens, cost, errors) for everything you ship.
• Keep solutions compliant with HIPAA and PHI requirements, including masking, access-controlled retrieval and prompt-injection protection.
• Work with operations leaders to find use cases worth building and prove their value.
• Mentor BI and ETL engineers and set up reusable standards for the team.

Must have

• Strong Python and SQL
• Azure OpenAI / AI Foundry, RAG, vector search, agents and tool calling
• Hands-on Databricks and/or Microsoft Fabric
• Experience evaluating and monitoring LLM solutions in production
• CI/CD and deployment on Azure

Good to have

• Understanding of Healthcare payer or provider data
• Semantic Kernel, LangGraph or AutoGen; MCP
• Classical ML and MLflow
• AI-102 or Databricks GenAI certification

In your first 12 months

• 2 - 3 AI use cases in production with measurable impact
• An evaluation and monitoring standard adopted by the team
• 3 - 5 internal engineers contributing to AI delivery