Senior DevOps Engineer (AWS, MLOps, Kubernetes) — Codvo · Pune

About the role

Senior DevOps Engineer for Codvo's AI / ML platforms — provision AWS with Terraform, run EKS clusters for ML workloads, and build MLOps and CI/CD pipelines with DevSecOps and GitOps. 5+ years, hybrid Pune (strong India candidates considered), INR 18-35 LPA band.

About this role and the team at Codvo. Senior DevOps Engineer for Codvo's AI / ML platforms — provision AWS with Terraform, run EKS clusters for ML workloads, and build MLOps and CI/CD pipelines with DevSecOps and GitOps. 5+ years, hybrid Pune (strong India candidates considered), INR 18-35 LPA band. This listing on cloudsoftsol.com is curated for engineers in India who are actively interviewing for senior cloud, DevOps and SRE roles. The role is permanent / full-time, hybrid, and the salary band reflects market rates in Pune (open to strong India candidates) as of mid-2026 (confirmed at the offer stage). If you are seeking a multi-year career platform rather than a stop-gap, this listing rewards depth — read the responsibilities and requirements below carefully and tailor your application to the specifics. Cloudsoft Solutions runs the leading AWS, Azure, GCP, DevOps, Kubernetes, Citrix and VMware training and placement programmes in Hyderabad and Bangalore — if you would like coaching for this exact role, mock interviews, resume review or salary-negotiation help, please contact us at info@cloudsoftsol.com. We do not charge candidates a fee for placement assistance; companies sponsor our involvement.

Responsibilities

Provision and manage AWS infrastructure with Terraform — VPC, EKS, S3, IAM, RDS, ECR and supporting services — as reusable, version-controlled modules. Build and operate scalable Amazon EKS clusters tuned for ML workloads, including GPU node groups, autoscaling, and platform add-ons via Helm. Develop MLOps pipelines and CI/CD for models — training, packaging, deployment, monitoring and automated retraining — integrating SageMaker and / or open-source ML tooling with the application delivery flow. Implement security scanning, GitOps (ArgoCD) delivery, secrets management, and cost optimisation across the AI platform. Support production reliability and rapid iteration for AI applications: observability with Prometheus / Grafana, SLOs, alerting and incident response. Mentor engineers, codify runbooks, and drive at least one FinOps / cost-reduction initiative per quarter.

Requirements & qualifications

5+ years of DevOps / Platform Engineering experience, with strong AWS and production Kubernetes (EKS preferred). Terraform proficiency — reusable modules, remote state, plan reviews. Scripting in Python and / or Go at automation-quality level. Hands-on CI/CD (GitHub Actions / Jenkins) and GitOps (ArgoCD / Flux). MLOps exposure — model CI/CD, SageMaker or comparable ML platforms, feature / model serving. DevSecOps practices: image / IaC scanning, secrets management, runtime policies. Strong fundamentals in Docker, Linux, networking and observability. AWS and CKA / CKAD certifications a plus.

Why this role in 2026

Codvo builds AI / ML products and platforms, so this DevOps role carries a genuinely modern mandate — you don't just run infrastructure, you own the MLOps backbone that gets models from prototype to production. For engineers who want to combine classic AWS / Kubernetes DevOps with hands-on MLOps and DevSecOps, it's a strong, fast-moving environment with direct impact on shipped AI products.

Application tips

Apply via the Codvo Freshteam link below. Lead with any MLOps or ML-platform work you have personally owned — model CI/CD, GPU scheduling on EKS, feature stores, model monitoring — even if your current title is plain DevOps. Quantify scale and reliability outcomes where you can.

Interview preparation

Expect a recruiter / screening call, a technical round on AWS + Kubernetes + Terraform, a hands-on exercise (Terraform module or a CI/CD + GitOps pipeline for a model), an MLOps-focused discussion (how you'd productionise and monitor a model), and a culture / hiring-manager round. Brush up on EKS GPU node groups, ArgoCD ApplicationSets, image signing, and model-drift monitoring.

Career growth

Track: Senior DevOps Engineer → Lead DevOps / MLOps Engineer → Platform Architect / Engineering Manager. The AWS + Kubernetes + MLOps combination is scarce and commands rising offers across the AI-products market.

Company & benefits

INR 18-35 LPA band (market-rate estimate; confirmed at offer). Flexible / hybrid work. Competitive salary, health cover, and a learning budget. High individual ownership and direct impact on AI products in a fast-moving engineering culture.