Apply

Ready to go for it?

AI Apply speeds things up—apply directly if you prefer.

FREE ACCESS
5,000–10,000 jobs/day
JobTailor Logo

See all jobs on JobTailor

Search thousands of fresh jobs every day.

Discover
  • Fresh listings
  • Fast filters
  • No subscription required
Create a free account and start exploring right away.
Work Life Group

Lead DevOps Engineer – Data & AI Platform

Work Life Group

Lead DevOps Engineer responsible for AI-assisted development in a data and AI platform. Focusing on modern DevOps practices and platform engineering with high automation.

Posted 5/28/2026full-timeRemote • CzechiaSeniorWebsite

Tech Stack

Tools & technologies
AirflowAzureCloudPythonSQL

About the role

Key responsibilities & impact
  • Define and implement a modern DevOps and platform engineering strategy aligned with data and AI platform goals
  • Develop roadmaps that incorporate AI-assisted development, testing, and operations
  • Drive the evolution from traditional DevOps to intelligent, self-service platform capabilities
  • Continuously evaluate emerging technologies (e.g., GenAI, LLMOps, AIOps) and incorporate them where relevant
  • Design and optimize CI/CD pipelines using AI-assisted tools (e.g., code generation, test generation, pipeline optimization)
  • Integrate AI copilots and automation agents into development and deployment workflows
  • Implement intelligent quality gates (e.g., automated code reviews, anomaly detection in pipelines)
  • Enable self-healing pipelines and automated failure diagnostics where possible
  • Build scalable automation frameworks leveraging AI, scripting, and infrastructure as code
  • Analyze and optimize integrations across the Anglo American Data Platform

Requirements

What you’ll need
  • Strong experience with CI/CD tools (e.g., Azure DevOps, GitHub Actions)
  • Expertise in infrastructure as code (Bicep, ARM or similar)
  • Proficiency in scripting (PowerShell, Python, Bash)
  • Deep understanding of DevOps principles, Git workflows, and release strategies
  • Experience with Azure services and cloud-native architectures
  • Familiarity with data platforms (Databricks, ADF, Airflow, SQL, AAS or equivalent)
  • Hands-on experience or strong familiarity with AI-assisted development tools (e.g., GitHub Copilot, ChatGPT, code assistants)
  • MLOps / LLMOps concepts (model deployment, monitoring, versioning)
  • AIOps tools for monitoring and incident management
  • Experience integrating APIs or services for AI capabilities into workflows is a plus.

Benefits

Comp & perks
  • Flexible working hours
  • Professional development opportunities

ATS Keywords

✓ Tailor your resume
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
CI/CDinfrastructure as codescriptingDevOps principlesGit workflowsrelease strategiesAI-assisted development toolsMLOpsAIOpsAPI integration