DevOps Engineer

• 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)
• Build scalable automation frameworks leveraging AI, scripting, and infrastructure as code
• Analyze and optimize integrations across the Anglo American Data Platform
• Implement governance practices across pipelines, including policy-as-code and automated compliance checks
• Create and maintain clear documentation, including AI-assisted “how-to” guides and self-service enablement
• Collaborate with Data Delivery and platform teams to resolve issues efficiently

Lead DevOps Engineer, Data & AI Platform

• Lead the Platform Evolution: Design and operate our Kubernetes ecosystem (GKE, multi-cluster) with a focus on high availability and zero-downtime operations.
• Build "Paved Roads": Own and evolve our PaaS strategy, using GitOps (ArgoCD) and CI/CD (GitLab) to empower domain teams to deploy independently.
• Architect Reliability: Define and implement our observability strategy across metrics, logs, and tracing (Prometheus, VictoriaMetrics, OpenTelemetry).
• Drive Infrastructure-as-Code: Lead the automation of our infrastructure using Terraform, ensuring all resources are standardized and version-controlled.
• Own the Error Budget: Partner with engineering teams to establish and manage SLOs, SLAs, and incident management frameworks.
• Disaster Recovery Mastery: Design and participate in regular DR drills, implementing blue/green and active/passive strategies across regions to ensure service continuity.
• Innovate Operations: Proactively apply AI-driven approaches to improve operational efficiency and automated bottleneck detection.

Senior Site Reliability Engineer

• Migrate containerized applications from Docker Compose to Kubernetes (k3s).
• Design, build, and maintain secure CI/CD pipelines in Azure DevOps and GitLab CI/CD or Jenkins.
• Integrate security controls into the delivery process, including static code analysis, dependency scanning, container image scanning, secrets detection, image signing, vulnerability management, and release gates.
• Support deployment automation, environment promotion, rollback, traceability, and release reliability.
• Work closely with development, infrastructure, and security teams to improve automation, resilience, and secure delivery practices.
• Troubleshoot and resolve build, deployment, and runtime issues across CI/CD and Kubernetes environments.
• Document implemented solutions and contribute to good DevSecOps practices across the team.

Senior DevSecOps Engineer, Docker Compose, Kubernetes

Senior DevSecOps Engineer – CI-CD Pipelines

• Design, implement, and maintain CI/CD pipelines (Bitbucket Pipelines, etc.)
• Automate infrastructure using tools like Terraform, Ansible, OpenStack
• Set up monitoring, alerting, and observability (Prometheus, Grafana, ELK, etc.)
• Optimize build, test, and deployment processes for speed and reliability
• Work with developers to ensure packages are production-ready
• Drive improvements in system performance, security, and scalability
• Deliver the full virtualization-targeted Linux distribution
• Support incident response and post-mortem processes

Senior DevOps Engineer

• Design, implement, and maintain a scalable and secure cloud infrastructure.
• Develop and automate deployment processes, ensuring efficient and reliable delivery of software releases
• Collaborate with cross-functional teams to understand infrastructure requirements and optimize system performance
• Monitor system performance, troubleshoot and resolve issues in a timely manner
• Implement and maintain CI/CD pipelines and configuration management tools
• Ensure compliance with security best practices and data protection regulations
• Stay up to date with emerging technologies and provide recommendations for continuous improvement

• Partner with DevOps and application engineering teams to design and improve standardized infrastructure, deployment workflows, and CI/CD pipelines
• Build, operate, and continuously improve our containerized infrastructure, with a focus on reliability, scalability, and cost efficiency
• Bring deep expertise in Kubernetes and its ecosystem, helping define best practices and support adoption across engineering teams
• Manage and evolve cloud infrastructure on AWS, including compute, networking, and storage systems
• Improve observability, monitoring, and incident readiness across production systems
• Participate in a shared on-call rotation (approximately 1 week every 5 weeks), responding to and resolving production incidents
• Mentor teammates and share knowledge to improve engineering practices and operational maturity across the organization

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Lead DevOps Engineer, Data & AI Platform

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