Senior Devops Engineer

Role & responsibilities

Role Overview

Senior DevOps & MLOps Engineer

Key Responsibilities

• Manage and operate

  AWS EKS/Kubernetes

  platforms.
• Build and maintain

  CI/CD pipelines

  using GitHub Actions, TeamCity, and ArgoCD.
• Deploy and support

  AI/ML/Agentic applications

  on AWS.
• Implement

  GitOps

  and infrastructure automation practices.
• Manage AWS services including

  IAM, ECR, CloudWatch, S3

  , and networking.
• Build observability solutions using

  OpenTelemetry, CloudWatch, Grafana, Loki, and Splunk

  .
• Implement secure, scalable, and compliant cloud architectures.
• Support AI platforms involving

  LLM Gateways, Model APIs, Bedrock, SageMaker

  , and distributed workloads.
• Collaborate with development, security, platform, and data teams.
• Troubleshoot infrastructure, deployment, performance, and security issues.
• Mentor junior engineers and contribute to platform best practices.

Required Skills

Must Have

• 4+ years of experience in

  DevOps, Cloud Engineering, or Platform Engineering

  .
• Strong hands-on experience with

  Kubernetes (EKS preferred)

  .
• Experience with

  ArgoCD

  and GitOps workflows.
• Expertise in

  AWS services

  and IAM.
• CI/CD experience using

  GitHub Actions, Azure DevOps, or TeamCity

  .
• Experience with

  Terraform

  or Infrastructure as Code.
• Strong monitoring and observability experience (

  CloudWatch, Grafana, Loki, Splunk, OpenTelemetry

  ).
• Good understanding of cloud security and compliance.

MLOps / AIOps Experience (Any One)

• SageMaker
• MLflow
• Kubeflow
• Airflow
• Bedrock
• AgentCore

Good to Have

• Experience with Celery, LLM Gateway, Model Serving, and AI workload deployment.
• Python or Bash scripting.
• Knowledge of GxP, HIPAA, or EU AI Act requirements.

Certifications

Mandatory

• CKA / CKAD / CKS

  (At least one)

• Terraform Associate

Preferred

• AWS Solutions Architect / DevOps Engineer

What You'll Work On

• Client facing cutting edge large-scale AWS platforms
• AI/GenAI & Agentic application deployments
• Kubernetes & GitOps ecosystems
• Enterprise DevSecOps and MLOps platforms
• Regulated pharma and life sciences solutions