O pozici
Are you ready to join a cutting-edge Digital Solutions company and help shape the future of enterprise software?
Our client is advancing a world-class data and AI platform that powers decision-making across the entire mining value chain. Built on Azure and Databricks, thrir platform enables scalable data products, advanced analytics, and emerging AI capabilities—from digital twins to intelligent automation and natural language querying.
Co budeš dělat
- 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.
- Automate repetitive tasks using AI agents, prompt-based workflows, or orchestration frameworks.
- Enhance DevOps pipelines to support data products and AI/ML workloads (MLOps/LLMOps).
- Standardize reusable templates and pipeline components for platform-wide adoption.
- Analyze and optimize integrations across the Anglo American Data Platform, including:
o Databricks (data processing, workflows, DABs)
o Airflow (orchestration)
o Azure services (compute, storage, identity)
o Power BI / downstream consumption layers
- Support deployment patterns for AI/ML models, feature pipelines, and inference services.
- Enable end-to-end lifecycle management for AI applications (training → deployment → monitoring).
- Implement governance practices across pipelines, including policy-as-code and automated compliance checks.
- Manage access control and ensure secure DevOps practices across environments.
- Introduce AIOps practices for monitoring, alerting, and incident management.
- Ensure high availability, scalability, and observability of DevOps processes.
- Create and maintain clear documentation, including AI-assisted “how-to” guides and selfservice enablement.
Koho hledáme
- 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:
o AI-assisted development tools (e.g., GitHub Copilot, ChatGPT, code assistants)
o MLOps / LLMOps concepts (model deployment, monitoring, versioning)
o AIOps tools for monitoring and incident management
- Understanding of how AI can be applied to:
o Code generation and testing
o Pipeline optimization
o Incident detection and resolution
- Experience integrating APIs or services for AI capabilities into workflows is a plus.
- Experience with Azure cloud platform
- Knowledge of data and AI workload deployment patterns.
- Understanding of observability tools and practices.
- Strong ability to analyze complex systems and improve scalability and performance.
- Proven troubleshooting skills in DevOps and platform environments.
- Ability to work across technical and business teams.
- Strong communication skills, including documenting and explaining complex concepts.
- Experience enabling teams through tooling and best practices.
- Experience with governance frameworks, access control, and compliance.
- Ability to implement and enforce DevOps standards at scale.
