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