AI Services - India
Team: AI Services
Level: Senior Software Engineer II / Staff Engineer / Principal Engineer / Team Lead (based on experience)
About the role
The AI Services team builds the platform products that our customers use to run AI and ML workloads. We design the control plane, the APIs, and the automation that make those workloads easy to launch, scale, and operate at production quality. You'll own backend services and the automation behind them, and take new capabilities from an initial idea to something running in production.
What you'll do
- Build product capabilities end to end — APIs, control plane, provisioning, and lifecycle operations like upgrade, scale, and repair.
- Take a new requirement from idea to production: prototype it, work out the multi-tenant design, and ship it.
- Write backend services in Go — controllers, reconcilers, queues, and workflows that handle long-running work and recover from failure.
- Build Kubernetes operators and custom controllers for the workloads we run.
- Work with cloud infrastructure (AWS and others): compute, networking, storage, and identity.
- Add the metrics, logging, and health signals needed to operate the product in production.
- Review code and help other engineers on the team.
What we're looking for
Required
- 7+ years building production backend or infrastructure software
- Strong hands-on Kubernetes experience — controllers and the reconcile loop, CRDs, RBAC, networking, storage, Helm, and real debugging experience.
- Experience writing Kubernetes custom operators and working with the operator pattern.
- Experience building distributed systems: concurrency, retries and idempotency, partial failure, and multi-tenant isolation.
- Strong in Go or Python, with Go preferred.
- Good understanding of cloud services, AWS/OCI/Azure/GCP.
- Able to take a loose requirement, ask the right questions, and drive it to shipped.
Nice to have
- Experience with Slurm (Slinky), Kubeflow, MLflow, or similar AI/ML platform tooling.
- CKA / CKAD certification.
- Multi-tenant SaaS control plane experience — tenancy, quotas, RBAC.
- GPU infrastructure: NVIDIA GPU Operator, MIG, device plugins, scheduling.
- Basic React/TypeScript — enough to read the UI code and make a small change.
- Comfortable using AI coding tools (Claude Code or similar) to work faster, with the judgment to check the output.
