Infrastructure & DevOps Engineer - AWS SageMaker Unified Studio

Reposted 7 Days Ago
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Hyderabad, Telangana, IND
In-Office
Senior level
Artificial Intelligence • Information Technology
The Role
The role involves designing and managing cloud infrastructure for AWS SageMaker Unified Studio, automating deployment pipelines, and ensuring scalability and security of machine learning workflows.
Summary Generated by Built In

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 it's empowering global organizations or collaborating with trailblazing startups, we are committed to delivering advanced, impactful solutions that meet today’s most complex challenges.


Requirements

Location: Remote (India / UK)
Experience: 5-7 years
Employment Type: Full-time

About the Role

We are seeking a skilled Infrastructure & DevOps Engineer to support the development and deployment of AWS SageMaker Unified Studio, building on the existing SageMaker ecosystem. The role involves designing, automating, and maintaining cloud-native infrastructure that enables scalable, secure, and efficient machine learning workflows.

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).

Top Skills

Aws Sagemaker
Bash
Ci/Cd
CloudFormation
Cloudwatch
Docker
Go
Grafana
Kubernetes
Prometheus
Python
Terraform
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The Company
11 Employees

What We Do

Xenon7 delivers specialized AI operations, AI products and services. Our innovation practice helps you separate initiatives warranting business investment from hype. We operate free from the bloat, weight and pyramidal structure of legacy consulting firms. Xenon7 enables our clients to make better human and technology decisions, and ethically achieve more with less

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