AI Engineer

Job Title: AI Engineer (Platform Engineering Background) Contract : 6 -9 Months (with Possible extension) Location: Canary Wharf, UK Hybrid (2 days a week) Role Overview We are looking for a hands-on AI Tools Support Engineer with a strong Platform Engineering/DevOps background to support the setup, configuration, integration, administration, and adoption of modern AI-assisted development tools. This is a short-term, high-impact engagement focused on enabling engineering teams to effectively use AI-powered coding and security platforms. The ideal candidate will have experience working with developer platforms, cloud environments, CI/CD pipelines, GitHub ecosystem tools, and AI-assisted software development solutions. Key Responsibilities

• Configure, deploy, and support AI developer productivity tools such as:
• Cursor
• Claude Code
• OpenAI Codex / CodeX
• Manage onboarding, access provisioning, licensing, and user administration for AI tools.
• Integrate AI tools with development environments, source control systems, and enterprise platforms.
• Collaborate with Platform Engineering, Security, and Development teams to ensure smooth adoption.
• Troubleshoot tool-related issues and provide L1/L2 technical support.
• Create and maintain technical documentation, setup guides, SOPs, and knowledge base articles.
• Assist in defining governance, security controls, and best practices for AI tool usage.
• Support CI/CD and DevOps integrations involving AI-enabled development workflows.
• Conduct user enablement sessions, demonstrations, and training for engineering teams.
• Monitor usage, collect feedback, and recommend improvements to maximize productivity. Required Skills & Experience
• 6+ years of experience in Platform Engineering, DevOps, Developer Platforms, or Infrastructure Engineering. Hands-on experience with one or more of the following:
• Cursor
• Claude Code
• OpenAI Codex / AI-assisted coding platforms Strong understanding of:
• Git and GitHub Enterprise
• CI/CD pipelines
• Software Development Lifecycle (SDLC)
• Platform Engineering concepts
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Knowledge of scripting/automation using Python, Bash, or PowerShell.
• Familiarity with identity management, access controls, and enterprise tool integration.
• Strong troubleshooting and documentation skills. Preferred Qualifications
• Experience supporting developer productivity platforms at scale.
• Exposure to security and compliance requirements related to AI tools.
• Understanding of prompt engineering and AI-assisted software development workflows.
• Experience working with enterprise engineering organizations.