We are looking for a DevOps Lead Engineer to design, build, and scale our cloud infrastructure and CI/CD ecosystem.

The ideal candidate should have strong AWS expertise (including Control Tower, Step Functions, and Lambda) along with automation and integration skills in Python.

Exposure to GenAI-based automation or ML pipeline deployment is a strong plus.

Responsibilities :

- Lead and own the DevOps strategy, architecture, and implementation across environments (Dev, QA, Prod).

- Design and manage AWS environments using AWS Control Tower, Organizations, Service Catalog, and Step Functions for orchestration and governance.

- Implement and optimize CI/CD pipelines using tools like GitHub Actions, Jenkins, or Azure DevOps.

- Automate provisioning and configuration using Terraform / CloudFormation.

- Integrate Python-based automation scripts for deployments, monitoring, and cloud operations.

- Collaborate with Data and AI teams to deploy GenAI models and APIs securely and efficiently.

- Manage containerization and orchestration using Docker and Kubernetes (EKS preferred).

- Ensure security, compliance, and cost optimization across multi-account AWS setups.

- Drive observability using CloudWatch, Grafana, or Prometheus for proactive monitoring and alerting.

- Mentor and guide junior DevOps engineers; establish best practices for infrastructure-as-code, branching, and release management.

Requirements :

- 7+ years in DevOps, Cloud, or Platform Engineering roles.

- Strong hands-on experience with AWS services : EC2 Lambda, S3 CloudFormation, IAM, Control Tower, Step Functions, and CloudWatch.

- Proven experience with Terraform, Python, and CI/CD tools (GitHub Actions, Jenkins, etc.

- Knowledge of Kubernetes / EKS and container orchestration best practices.

- Familiarity with ML/GenAI pipelines or deployment of AI APIs in production.

- Strong grasp of networking, security groups, IAM policies, and least-privilege access design.

- Excellent problem-solving and communication skills.

Nice-to-Have :

- Experience with Databricks, SageMaker, or AI model deployment frameworks.

- Exposure to Azure or GCP cloud environments.

- Scripting knowledge in Bash or Go in addition to Python.

- Familiarity with monitoring and cost optimization tools like CloudHealth, Datadog, or New Relic.

Desired Skills and Experience :

AWS,CI - CD,Python,Terraform