Infrastructure & DevOps Engineer - AWS SageMaker Unified Studio

About us: Where elite tech talent meets world-class opportunities! At Xenon7, we work with leading enterprises and innovative startups on exciting, cutting edge projects that leverage the latest technologies across various domains of IT including Data, Web, Infrastructure, AI, and many others. Our expertise in IT solutions development and on-demand resources allows us to partner with clients on transformative initiatives, driving innovation and business growth. Whether its empowering global organizations or collaborating with trailblazing startups, we are committed to delivering advanced, impactful solutions that meet today s most complex challenges.

Location:

About the Role

Infrastructure & DevOps Engineer

You will collaborate with data scientists, ML engineers, and platform teams to ensure seamless integration of new features into Unified Studio, focusing on reliability, automation, and operational excellence.

Key Responsibilities

• Design and implement

  cloud infrastructure

  to support SageMaker Unified Studio features.
• Automate deployment pipelines using

  CI/CD tools

  (CodePipeline, Jenkins, GitHub Actions, etc.).
• Manage

  infrastructure as code (IaC)

  with Terraform/CloudFormation.
• Ensure

  scalability, security, and compliance

  of ML workloads in AWS.
• Monitor and optimize

  SageMaker Studio environments

  , including notebooks, pipelines, and endpoints.
• Collaborate with ML engineers to integrate

  new Unified Studio capabilities

  into existing workflows.
• Implement

  observability solutions

  (CloudWatch, Prometheus, Grafana) for proactive monitoring.
• Troubleshoot infrastructure and deployment issues across distributed ML systems.
• Drive

  DevOps best practices

  for automation, testing, and release management.

Qualifications

• Bachelor s degree in Computer Science, Engineering, or related field.

• 3-5 years of experience

  in Infrastructure/DevOps roles.
• Strong expertise in

  AWS services

  : SageMaker, EC2, S3, IAM, CloudFormation, Lambda, EKS.
• Hands-on experience with

  CI/CD pipelines

  and automation frameworks.
• Proficiency in

  Terraform, CloudFormation, or Ansible

  for IaC.
• Solid understanding of

  Docker & Kubernetes

  for containerized ML workloads.
• Familiarity with

  ML workflows

  and SageMaker Studio (preferred).
• Strong scripting skills in

  Python, Bash, or Go

  .
• Experience with

  monitoring/logging tools

  (CloudWatch, ELK, Prometheus).
• Excellent problem-solving and communication skills.

Preferred Skills

• Exposure to

  SageMaker Unified Studio

  or similar ML orchestration platforms.
• Knowledge of

  data engineering pipelines

  and ML lifecycle management.
• Experience working in

  financial services or regulated industries

  (bonus).