AI DevOps Engineer
Posted 3 days ago by Insight International (UK) Ltd
Negotiable
Undetermined
Hybrid
Sheffield, England, United Kingdom
Summary: The AI DevOps Engineer role in Sheffield, UK, focuses on the end-to-end software delivery lifecycle, emphasizing Infrastructure as Code (IaC), CI/CD, and system reliability. The position requires a strong understanding of enterprise environments and the ability to manage deliverables independently while supporting GenAI-enabled engineering practices. The role involves designing and maintaining CI/CD pipelines, automating infrastructure, and ensuring compliance with enterprise controls. Collaboration with developers and IT operations is essential to streamline releases and troubleshoot issues.
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)
- Implement guardrails for GenAI usage aligned to enterprise policies
- Support reliability and observability for GenAI-enabled services
Key Skills:
- Scripting/Programming: Bash, Python, Shell
- CI/CD Tools: Jenkins, GitLab CI, Azure DevOps
- Containerization: Docker, Kubernetes
- 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 and safe application in engineering workflows
- GenAI Tooling & Integration: Experience using and integrating GenAI-assisted tools into workflows
- Responsible AI & Data Handling: Awareness of privacy, IP, data classification, and secure usage patterns
Salary (Rate): undetermined
City: Sheffield
Country: United Kingdom
Working Arrangements: hybrid
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Role: AI DevOps Engineer
Location: Sheffield, UK (Hybrid)
Hiring type: Contract Role
Role Focus
- End-to-end software delivery lifecycle
- 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
- CI/CD Tools: Jenkins, GitLab CI, Azure DevOps
- Containerization: Docker, Kubernetes
- 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)