Senior DevOps Engineer - Docker/Kubernetes

Sr. DevOps EngineerObservability Strategy (Web & AI Applications) :

• Design and implement an end-to-end observability & alert stack covering both traditional web applications and AI/ML services.

• Develop and maintain tooling such as Prometheus, Grafana, ELK/OpenSearch, Datadog, or equivalent.

• Build AI-specific observability : model latency/throughput tracking, GPU utilization, token usage, drift detection, and inference quality signals.

Infrastructure Scaling & Reliability :

• Design and manage infrastructure capable of scaling across on-premise data centers and public cloud.

• Own capacity planning, load testing, auto-scaling, and cost-optimization initiatives across compute, storage, and networking.

• Implement Infrastructure as Code (Terraform, Ansible, or equivalent) to ensure environments are reproducible, version-controlled, and auditable.

• Lead disaster recovery, backup, and high-availability strategy for critical systems.

DevOps & CI/CD Delivery :

• Partner closely with Solution Architects to translate project and system designs into concrete DevOps execution plans.

• Design, build, and maintain CI/CD pipelines (Jenkins, GitHub Actions or ArgoCD/Flux for GitOps) across multiple projects and teams.

• Containerize and orchestrate applications using Docker and Kubernetes, including Helm chart and manifest management.

• Embed security and compliance checks (SAST/DAST, secrets scanning, image scanning) directly into the delivery pipeline (DevSecOps).

GPU Infrastructure & Model Deployment :

• Provision, configure, and manage GPU infrastructure (on-prem clusters and cloud GPU instances) for model training and inference.

• Deploy, scale, and monitor ML/LLM models in production using tools such as Triton Inference Server, vLLM, or similar.

• Optimize GPU utilization, cost, and throughput across multi-tenant workloads; manage CUDA/driver/toolkit versions.

• Collaborate with data science/ML engineering teams on MLOps pipelines model versioning, experiment tracking, and model registry.

Requirements :

• 5-10 years of hands-on DevOps/SRE/Infrastructure engineering experience, including at least 23 years in a senior or lead capacity.

• Deep expertise in Git-based workflows and repository management at scale (GitHub/GitLab/Bitbucket).

• Proven experience designing observability stacks (Prometheus, Grafana, ELK/EFK, Datadog, New Relic, OpenTelemetry).

• Strong background in cloud platforms (AWS, Azure, and/or GCP) and on-premise/hybrid infrastructure.