Lead DevOps & Platform Engineer - NuPlay (Nurix AI)

Overview

Lead the platform that every NuPlay AI product runs on, covering cloud, Kubernetes, GPU inference, observability, incident response and access control. First lead the move from AWS to Azure without dropping a call. This is a hands-on lead role.

What you'll do

• Design landing zones, multi-region networking (hub-and-spoke, Private Link, NAT, layered trust zones) and HA/DR against defined RPO and RTO targets.
• Lead the AWS to Azure migration and run both clouds safely in between.
• Keep everything as code in Terraform.
• Run EKS and AKS clusters for microservices, real-time voice pipelines and GPU serving of fine-tuned LLMs.
• Autoscale for call peaks, hold the voice latency budget, and track GPU cost per call minute.
• Build observability across the application, data and model layers: metrics, logs, traces, and SLOs per product and per tenant.
• Set up on-call, severity levels, incident command, customer status updates and blameless RCAs.
• Feed alerts into the agents' auto-heal loops.
• Ship each sub-product as shared multi-tenant SaaS, as a dedicated tenant stack, or into a customer's own cloud, all from one codebase and one pipeline.
• Run RBAC and just-in-time access for internal staff across clusters, databases, vector stores, logs and call recordings, with full audit trails.
• Own the infrastructure controls and evidence for SOC 2 and ISO audits.
• Keep the auth service highly available.
• Own CI/CD and GitOps across all sub-products, with safe rollouts and fast rollbacks.
• Build internal tooling in code and review service designs so they scale and fail well.
• Lead and grow the DevOps team: hire, mentor, and set the standards for infrastructure and on-call.
• Act as the bridge between product engineering and infrastructure.

What you'll need

• 8 to 12 years in total experience, starting as a backend engineer shipping production services in Python, Go, Java or Node.js.
• At least 3 years leading an infrastructure, platform or SRE charter.
• Designed, not just operated, production cloud on AWS, all in Terraform or an equivalent.
• Hands-on Azure experience (AKS, VNets, Entra ID, Private Link), or experience leading a cloud-to-cloud migration.
• Deep production Kubernetes: multi-cluster operations, networking and ingress, service mesh, stateful workloads, GitOps (Argo CD or Flux), and autoscaling with HPA, KEDA or Karpenter.
• Built observability and incident processes others relied on: OpenTelemetry, Prometheus and Grafana or Datadog, SLOs and error budgets, on-call rotations and RCAs.
• Run multi-tenant SaaS for enterprise customers: IAM, RBAC, secrets management, network isolation and audit logging.
• At least one year running AI products in production.

Nice to have

• Real-time voice infrastructure: SIP, WebRTC, telephony carriers and per-hop latency budgets.
• GPU inference for LLMs: vLLM, TensorRT-LLM or Triton, GPU scheduling and cost control.
• Search, vector and streaming systems in production: OpenSearch, Weaviate or pgvector, Kafka.
• Identity and compliance: Keycloak, OIDC and SAML; SOC 2, ISO 27001, ISO 42001, HIPAA, GDPR or India's DPDP Act audits.
• CKA, CKS or Azure Solutions Architect Expert certification.

Details

• Location: Bangalore, India.
• Employment type: Full-time.