DevOps Engineer

Overview Infrastructure as Code (IaC), CI/CD, monitoring, and system reliability Strong understanding of enterprise environments, controls, and compliance requirements Ability to manage work and deliverables independently Ability to support GenAI-enabled engineering practices (e.g., AI-assisted development/operations) while adhering to enterprise governance, security, and risk controls Key Responsibilities Design, implement, and maintain CI/CD pipelines (e.g., Jenkins) Automate infrastructure provisioning and configuration (e.g., Ansible, Terraform) Ensure high availability, scalability, and security of systems Collaborate with developers, QA, and IT operations to streamline releases Troubleshoot deployment, build, and infrastructure issues Maintain configuration management tools (Ansible) Ensure compliance with enterprise controls and regulatory requirements Work independently to deliver on assigned tasks and projects Utilize Jira and Confluence for work tracking and documentation Enable and operationalise GenAI/LLM-based tooling in the DevOps toolchain (where approved), including secure access, environment configuration, and integration into CI/CD workflows Implement guardrails for GenAI usage (e.g., data handling, prompt/content logging where required, secrets protection, model/tool access controls) aligned to enterprise policies Support reliability and observability for GenAI-enabled services (e.g., monitoring latency, error rates, cost/usage, and drift/quality signals where applicable) Core Skills Scripting/Programming: Bash, Python, Shell Infrastructure as Code: Ansible, Terraform Source Control: Git, Bitbucket Security & Compliance: Understanding of DevSecOps, secrets management, enterprise controls, and compliance Familiarity with Jira and Confluence GenAI/LLM Fundamentals: Understanding of LLM concepts (prompting, embeddings, RAG, model limitations), and how to apply them safely in engineering workflows GenAI Tooling & Integration: Experience using and integrating GenAI-assisted tools (e.g., code assistants, chat-based ops assistants) and/or APIs into developer/DevOps workflows Responsible AI & Data Handling: Awareness of privacy, IP, data classification, and secure usage patterns when working with GenAI tools in enterprise environments Preferred Experience supporting GenAI platforms/services in production (e.g., model/API deployment patterns, prompt/version management, evaluation/monitoring, and cost controls) #J-18808-Ljbffr