Senior DevOps Engineer

About Tarento: Tarento is a fast-growing technology consulting company headquartered in Stockholm, with a strong presence in India and clients across the globe. We specialize in digital transformation, product engineering, and enterprise solutions, working across diverse industries including retail, manufacturing, and healthcare.

Our teams combine Nordic values with Indian expertise to deliver innovative, scalable, and high-impact solutions. We're proud to be recognized as a Great Place to Work , a testament to our inclusive culture, strong leadership, and commitment to employee well-being and growth. At Tarento, you’ll be part of a collaborative environment where ideas are valued, learning is continuous, and careers are built on passion and purpose.

Role Overview We are looking for a Senior DevOps Engineer with 3+ years of experience in Multi-Cloud, Kubernetes, Jenkins, and automation. The role involves building and managing scalable infrastructure, driving automation, supporting migrations, and collaborating with clients.

Key Responsibilities

Design, build, and maintain cloud infrastructure (AWS/GCP/Azure) using IaC (Terraform/Pulumi/Cloud. Formation) Architect and manage CI/CD pipelines for application and ML model deployment Build and maintain Kubernetes clusters; manage containerized workloads for services and ML inference Own observability stack — logging, metrics, tracing, alerting (Prometheus, Grafana, ELK/EFK, Datadog) Support ML lifecycle infrastructure: feature stores, model registries, training pipelines, GPU cluster management Manage GPU/accelerator provisioning and cost optimization (spot instances, autoscaling, reserved capacity) Drive security best practices — IAM, secrets management, network policies, compliance (SOC2/ISO) Lead incident response, on-call rotations, and postmortems; drive SRE culture (SLOs/SLIs) Mentor junior engineers; collaborate with data science/ML teams on infra requirements Manage multi-region/multi-cloud deployments and disaster recovery strategy Own capacity planning, cost governance (Fin.

Ops) across cloud + ML compute Required Skills & Experience: Cloud Platforms Deep expertise in at least one hyperscaler (AWS/GCP/Azure), working knowledge of a second Compute, networking (VPC, load balancers, CDN), storage, IAM Infrastructure as Code & Automation Terraform / Pulumi / Cloud. Formation Ansible / Chef / Puppet Git.

Ops (ArgoCD/Flux) Containers & Orchestration Docker, Kubernetes (EKS/GKE/AKS or self-managed) Helm, Kustomize Service mesh (Istio/Linkerd) — good to have CI/CD Jenkins, GitLab CI, GitHub Actions, ArgoCD, CircleCI Observability & Reliability Prometheus, Grafana, Alertmanager ELK/EFK stack, Loki Datadog/New Relic Distributed tracing (Jaeger/Open.

Telemetry) Security Vault/Secrets Manager, IAM policy design Network security, container security (Trivy, Falco) Compliance frameworks Scripting/Programming Python (strong — for automation & ML tooling integration) Bash/Go (good to have) Databases & Messaging SQL/NoSQL operations at scale (Postgres, MongoDB, Redis) Kafka/RabbitMQ/Pub-Sub for streaming ML data pipelines Preferred Qualifications: Certifications: AWS/GCP/Azure Solutions Architect, CKA/CKAD Experience running LLM inference infrastructure at scale (vLLM, TGI, quantization-aware serving) Experience with cost optimization for large-scale GPU training Contributions to open-source infra/MLOps tooling Education: BE/BTech , Information Technology, or related discipline.