Description
Description
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.
Location: Remote (Europe)
Experience: 6+ years
Employment Type: (Contractor/Full-time)
Overview
The Sagemaker DevOps Engineer acts as the bridge between standard infrastructure and the specialized needs of Machine Learning (ML). Your primary goal is to take the "manual" out of ML. You will be responsible for architecting the environment (SageMaker), ensuring it scales across an enterprise, and automating the journey a model takes from a developer's laptop to a production environment.
Responsibilities
- Build DevOps automations to setup Sagemaker Unified Studio for enterprise
- Implement Sagemaker Lifecycle configurations
- Create CICD pipelines for end-users to deploy custom Docker images & Kernels in Sagemaker
- Build alert & monitoring capabilities for Sagemaker projects to control costs and service quotas
- MLOps automations for model and infrastructure deployments to higher environments
Requirements
- From 6+ years of experience in a relevant role
- Expert level in AWS and Python
- Working knowledge with Sagemaker
- Experience building DevOps automations for enterprise
- Preferred to have experience building Jenkins pipelines
- Preferred to have experience with MLOps automations
Company
Xenon7 helps organizations deploy AI through orchestration, turning agent capabilities into measurable workflow acceleration. It operates at the orchestration layer where tools, systems, and people coordinate, delivering fixed-scope sprints that ship production-grade agent workflows and the architecture to scale them. Services include activating existing AI platforms (Copilot, Gemini, Claude Projects, etc.), building agents inside enterprise suites, and engineering and operating the orchestration layer. Each sprint is staffed by an Orchestration Architect, AI Engineer, and AgentOps Commander, with governance, telemetry, and KPI instrumentation.
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