DevSecOps Engineer — AI Platform

2 days WFH About the role You will be the main hands-on engineer across the full lifecycle of an AI-powered document processing and case intelligence platform on AWS GCC. This spans development and platform engineering; it is not a backend-only role. You will work with the business owner, business analyst and solution architect to translate user stories into technical requirements, and take ownership of end-to-end infrastructure and security solutions across the products and relevant systems. 12-month contract with an optional 12-month extension. Key responsibilities • Work with the business owner, business analyst and solution architect to translate user stories into technical requirements • Develop and maintain API integrations with the case management system and any other required systems • Design and build the agentic AI pipeline, including LLM API integration, prompt engineering, skill and context design, structured output schemas, confidence scoring and error handling • Work with the Software Quality Engineer to develop automation and processes to deploy, manage, scale and monitor applications in data centre and cloud environments • Troubleshoot and resolve system and application issues, participating in on-call escalations for critical incidents • Take ownership of end-to-end infrastructure and security solutions across the products and relevant systems • Deploy and manage monitoring tools to track infrastructure performance, utilisation and health • Configure and maintain CI/CD pipelines, incorporating streamlined change management and release processes • Develop scripts and automation tools to support software build, integration and deployment across development and production environments • Plan, implement and monitor system security architecture, including threat and risk assessments About you • Minimum 4 years' relevant working experience • Degree or diploma in Computer Science, Computer or Electronics Engineering, IT or a related discipline • Passion for automation, standardisation and best practices in infrastructure and security • Strong understanding of the Software Development Life Cycle (SDLC), Test-Driven Development (TDD), Continuous Integration (CI) and Continuous Delivery (CD) • Track record in agentic AI system design: multi-agent pipelines, Bedrock AgentCore, orchestration and MCP Server, RAG knowledge bases, human-in-the-loop architecture • Experience working with high-availability, high-performance and high-security multi-data-centre systems and hybrid cloud environments • Proficiency in PowerShell and Python • Experience with Git and modern branching workflows • Strong understanding of container technologies (Docker, Kubernetes) • Experience with CI/CD pipelines (GitHub Actions, GitLab CI) • Significant advantage • Experience in regulatory or compliance contexts where agent outputs must be accurate, auditable and structured for expert reviewers Added advantage • Security certifications such as CREST, CISSP, CISM or relevant cloud security credentials • Experience working in an organisation that successfully implemented a DevSecOps transformation • Hands-on experience with API security, secrets management and zero-trust architectures • Experience developing and deploying systems on GCC