Data Scientist

IndiGo (InterGlobe Aviation Ltd); Gurugram District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

IndiGo (InterGlobe Aviation Ltd) is seeking a Data Scientist to drive autonomous AI agents, GenAI, and knowledge-graph based systems for airline solutions.

The role covers end‑to‑end development—from problem discovery to enterprise-scale deployment—using Microsoft Foundry, Azure AI, and FastAPI to deliver production AI capabilities. Gurgaon office; hands‑on ownership expected.

Qualifications

• Bachelor’s degree in engineering or mathematics with strong AI/ML background.
• Hands‑on experience building production AI/ML systems.
• Proficiency in Python and modern AI frameworks.

Responsibilities

• Design, build, and scale production‑grade AI systems and agents.
• Develop AI solutions using Microsoft Foundry and Azure services.
• Integrate AI into enterprise systems with robust APIs and workflows.
• Collaborate across product, data, and platform teams from prototype to production.
• Ensure scalable, secure, and cost‑efficient AI services.

Skills

Python

Agentic AI / autonomous AI

LLMs / GenAI

Microsoft Foundry / Azure AI

Knowledge graphs

REST APIs

FastAPI

LangChain

Education

Bachelor’s in Engineering or Mathematics

Tools

Microsoft Foundry

Azure ML

Azure AI services

Azure OpenAI

APIs & Integration

Job description

Data Scientist

Drive cutting-edge research and development in autonomous AI agents, Agentic AI, and GenAI systems to power next-gen airline solutions.

Job Title & Summary

Data Scientist Drive cutting-edge research and development in autonomous AI agents, Agentic AI, and GenAI systems to power next-gen airline solutions.

Role Summary

• Design, build, and scale production‑grade AI systems, including autonomous AI agents, for Lab37’s innovation and enterprise AI platforms.
• Work on Agentic AI, GenAI, Knowledge Graph–driven systems, and data intelligence layers, leveraging Microsoft Foundry as the core AI platform, across customer, operations, and commercial airline use cases.
• Contribute end‑to‑end—from problem discovery and prototype to enterprise‑scale production deployment.

Key Responsibilities

• Design and implement autonomous AI systems including decision agents, workflow agents, and self‑orchestrating AI components.
• Build and manage knowledge graphs and data intelligence layers to enable contextual reasoning, semantic search, and intelligent decision‑making.
• Develop and deploy AI solutions using Microsoft Foundry for model lifecycle management, orchestration, and enterprise integration.
• Develop Agentic AI solutions that leverage structured and unstructured data for real‑time insights.
• Design and implement AI/ML and GenAI solutions aligned with Lab37’s roadmap and airline business priorities.
• Build robust APIs and backend services for AI models using Python and FastAPI.
• Integrate AI solutions with enterprise systems, internal platforms, and cloud services.
• Ensure scalability, reliability, security, governance, and cost efficiency of AI services.
• Collaborate with product, data, and platform teams to move ideas from POC → MVP → Production.
• Required Skills / Must-Have

Required Skills / Must-Have

Programming: Strong proficiency in Python.

AI / ML: Hands‑on experience with autonomous AI, Agentic AI systems, LLMs, and GenAI.

Microsoft AI Ecosystem: Strong hands‑on experience across the Microsoft AI ecosystem, including Microsoft Foundry, Azure AI Services, Azure OpenAI, and Azure ML.

Knowledge Graphs & Data Intelligence: Experience working with knowledge graphs, embeddings, semantic layers, and data intelligence platforms.

Frameworks & Tools: FastAPI, LangChain or equivalent GenAI frameworks.

Cloud: Practical experience with Microsoft Azure (Azure ML, Azure AI services preferred).

APIs & Integration: REST APIs, event‑driven or microservices‑based architectures.

• Nice-to-Have / Preferred Skills
• Experience with airline industry datasets or operational systems.
• Familiarity with Reinforcement Learning (RL) and multi‑agent systems.
• Knowledge of MLOps practices and CI/CD for ML workflows.
• Contributions to open‑source AI projects or publications in top‑tier conferences.
• Education & Qualifications
• Bachelor’s in Engineering or Mathematics with strong AI/ML experience.
• Hands‑On Expectation
• This is a hands‑on engineering role. Candidates are expected to actively design, build, test, deploy, and support AI solutions end‑to‑end.
• The role requires practical, production‑level experience across the Microsoft AI ecosystem, including Microsoft Foundry, Azure AI services, and model integration into enterprise systems.
• Candidates must be comfortable working on real codebases, real data, and real production constraints, not limited to research, advisory, or high‑level design roles.
• Profiles focused only on theoretical AI, presentations, or vendor‑driven implementations without hands‑on ownership are not suitable for this role.
• Strong ownership mindset is expected—from POC → MVP → scalable production deployment.
• Location & Work Mode

Gurgaon – Work from office