Senior DevOps Engineer

Responsibilities:

• Cloud Architecture and Orchestration: Design and manage multi-cloud environments (AWS/GCP) using Terraform to ensure infrastructure is versioned, reproducible, and scalable.
• Kubernetes Mastery: Oversee production-grade Kubernetes clusters, focusing on cluster health, resource optimisation, and seamless application deployment.
• AI and Data Infrastructure: Build and maintain the specialised infrastructure required for AI workloads.
• Database Management: Maintain a diverse data layer, including Vector search databases (for AI retrieval), PostgreSQL, MySQL, and MongoDB.
• Observability and Reliability: Implement deep-stack monitoring and alerting using Datadog and Prometheus to ensure proactive issue detection and resolution.
• Automation-First Mindset: Maintain and evolve an active codebase in Python, Go, or Bash to automate repetitive tasks. You will also integrate LLMs into your workflow to accelerate scripting, documentation, and operational efficiency.
• Networking and Traffic: Manage complex cloud networking topologies, including VPCs, Load Balancing, Service Meshes, and Caching layers (e. g., Redis) to minimise latency.
• Incident Response: Lead the debugging of complex, distributed systems issues, performing root cause analysis to prevent recurrence, as part of an on-call rotation.

Requirements:

• Experience: 6+ years of experience in Infrastructure, DevOps, or Site Reliability Engineering, with at least 5 years focused on cloud-native environments.
• Linux Systems: Solid understanding of Linux administration and performance tuning. You are comfortable navigating the command line to diagnose system-level issues.
• Infrastructure as Code: Expert-level experience with Terraform (or OpenTofu) and managing state at scale.
• Containerization: Proven track record of managing Kubernetes in a production environment (EKS, GKE, or self-managed).
• Software Engineering: Strong proficiency in Python or Go. You treat infrastructure code with the same rigour as application code (testing, PR reviews, CI/CD).
• Data Systems: Hands-on experience managing relational and non-relational databases.
• PaaS & Serverless: Experience leveraging and securing PaaS offerings to speed up development cycles.
• AI-Augmented Engineering: Practical experience using LLMs (GitHub Copilot, ChatGPT, Claude) to increase your personal and team productivity.