Applied AI Engineer & Data Specialist

Reliance Intelligence is the deep-tech AI venture of Reliance Industries, on a mission to make Artificial Intelligence accessible, trusted, and affordable for 1Bn+ Indians. We're not bolting AI onto legacy infrastructure — we're building India's sovereign AI backbone from first principles: gigawatt-scale, powered entirely by clean energy, and engineered to be one of the largest AI platforms anywhere in the world.

On this foundation, our AI services will work in 22 Indian languages and span consumer, enterprise, devices, and social good built around one principle: AI must be easy to use, trusted to rely on, and affordable for all. We're building a world-class team of researchers, engineers, PMs, and technology leaders, and partnering with global technology players, universities, and research institutions to shape the future of intelligence, for the world, from India.

The Role

We're looking for an Applied AI Engineer & Data Specialist (Decision Intelligence) to turn raw retail signals into reasoning systems, so the platform learns continuously from field deployments. You'll work closely with the Platform Architects and Domain Pod teams to improve buying, pricing, and working capital decisions by turning field behaviour into reusable intelligence.

This is an AI-native, hands-on, 0-to-1 build organization. Everyone here is hands-on — there are no manager-only seats — and roles differ by problem focus, not by SDLC phase ownership. There's no handoff between Product, Engineering, QA, Data, and Ops: you're expected to design, build, test, deploy, and observe within your own domain, comfortable with ambiguity every step of the way.

What You'll Do

• Build demand forecasting pipelines, decision policies, and optimization + inference loops.
• Build event pipelines from Shop OS and feature stores for continuous learning.
• Build feedback ingestion pipelines for model tuning.
• Apply real-time analytics and streaming systems to live retail data.
• Turn field behaviour into reusable intelligence across the platform.

What We're Looking For

• 4-8 years in real-time analytics/streaming systems, with applied ML in production (not research-only.)
• Hands-on experience building with LLMs / AI agents / ML systems in production (not just prototyping.)
• Strong Kafka/Spark/Databricks, data contracts, and observability pipeline experience.
• Comfort with ambiguity and a fast-moving, 0-to-1 environment — we ship weekly, not quarterly.
• Bonus: experience with Python, Tableau/Looker Studio/GA, feature pipelines, and experimentation frameworks.