Senior Engineer, Devops (AWS Automation)

Overview

Own production ML environments and MLOps infrastructure within the infrastructure and data science teams, supporting day-to-day operations, ad-hoc requests and cross-team projects.

What you'll do

• Architect and productionize microservices with advanced DevOps pipelines, partnering with data science and ML teams to optimize model serving on Kubernetes platforms with service mesh.
• Architect scalable MLOps pipelines using AWS services such as SageMaker, EMR and OpenSearch.
• Design comprehensive observability frameworks to minimize MTTR and ensure 24x7 platform reliability.
• Engineer secure, automated CI/CD workflows with governance and compliance controls.
• Lead 24x7 on-call engineering, CDN and security hardening, and cost optimization strategies for IaaS and PaaS in cloud.
• Manage infrastructure operations, production deployments and hybrid cloud environments.
• Drive cross-functional collaboration with development, QA, operations and data teams across global time zones to scale OpenSearch/EMR platforms and platform operations.

What you'll need

• 4.5+ years (Sr. Engineer) / 7+ years (Module Lead) of AWS/DevOps production experience.
• Scripting in Python, Bash, Groovy or Java (CI/CD, EKS, FastAPI/Spring Boot).
• CI/CD tooling: Jenkins (declarative pipelines, Groovy), Spinnaker, CodePipeline/CodeBuild, Gradle, Maven, Artifactory, GitHub Actions.
• Infrastructure as code: Terraform, AWS CloudFormation.
• Containers: EKS with Istio/Gloo/Karpenter, ECS, Docker, Buildah.
• AWS: VPC, IAM, GuardDuty, AWS Config, S3, DynamoDB, Lambda, SageMaker, EMR, cost optimization.
• Observability: Splunk, CloudWatch, Prometheus/Grafana, New Relic, Azure Monitor.
• GitHub: Actions automation, branch/PR governance.
• DNS management: NS1, Cloudflare or GoDaddy.

Details

• Location: Noida, Uttar Pradesh, India.
• Work mode: Hybrid (#LI-Hybrid).
• Experience level: Sr. Engineer, DevOps AWS (Automation), 4.5+ years.