DevOps/AI Engineer
Role details
Job location
Tech stack
Job description
DevOps/AI Engineer
My client, a large consultancy, is in need of a DevOps/AI Engineer for a 6 month contract inside IR35 based in Sheffield, offering 2 days per week remote but requiring 3 days per week on-site.
The ideal candidate will have strong experience in 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 (eg, 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 (eg, model/API deployment patterns, prompt/version management, evaluation/monitoring, and cost controls)
Requirements
The ideal candidate will have strong experience in 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 (eg, 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 (eg, model/API deployment patterns, prompt/version management, evaluation/monitoring, and cost controls)
