Agentic SDLC Engineer

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 Agentic SDLC Engineer (DevEx + AI-Native Delivery) to own how software gets built using agents, and make the token economy real. You'll work closely with every engineering pod across the build organization to deliver 3-5x engineering velocity without quality loss, running 10x cheaper than competitors.

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 prompt-to-code pipelines, auto test generation, and spec-to-working-system flows.
• Own model routing, GPU utilization strategy, and edge vs. cloud inference balance.
• Ship production infrastructure as code across the platform.
• Enforce agentic SDLC processes across engineering pods.
• Continuously push engineering velocity without compromising quality.

What We're Looking For

• 4-8 years in internal platform engineering, developer tooling, or CI/CD systems.
• Hands-on experience building with LLMs / AI agents / ML systems in production (not just prototyping.)
• Strong skills in Claude/Cursor skills & plugin development, MCP development, GitHub Actions/build systems, Terraform, and Kubernetes.
• Comfort with ambiguity and a fast-moving, 0-to-1 environment — we ship weekly, not quarterly.
• Bonus: GCP systems-level optimization and performance tuning experience.