Lead DevOps Engineer – Data & AI Platform

DevOps EngineerDevOps EngineerFull TimeRemoteSeniorTeam 11-50Since 2012H1B No SponsorCompany SiteLinkedIn

Location

Czechia

Posted

10 hours ago

Salary

0

Seniority

Senior

Bachelor DegreeEnglishAirflowAzureCloudPythonSQL

Job Description

Lead DevOps Engineer – Data & AI Platform

Work Life Group

• 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

Job Requirements

  • 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

  • Flexible working hours
  • Professional development opportunities

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