Senior Platform Security Engineer - AI Resilience & Security Enhancements (Contract)

In this hands-on contract role, you will strengthen the security and resilience of a modern engineering platform, with a particular focus on AI-enabled workflows and secure software delivery. You will work closely with platform, engineering, and security teams to design, prototype, and implement practical security controls. Your work will span secure autonomous agent execution, CI/CD security, production access management, container security, and software supply chain integrity. You will turn security requirements into reliable, maintainable tooling and workflows that developers can use in their day-to-day work. The role combines technical problem-solving, automation, and close collaboration with engineers to deliver measurable improvements to production systems. You will help improve security without compromising service availability or engineering productivity.

• Design, evaluate, and implement controls for secure autonomous AI agent execution, including policy enforcement, permissions, sandboxing, execution isolation, and auditability.

• Integrate security checks into CI/CD pipelines and pull request workflows to identify vulnerable or unsafe code changes before they are merged.

• Evaluate conventional security tools and AI-assisted code security approaches, assessing detection accuracy, false positives, potential bypasses, and developer usability.

• Strengthen production access controls through least-privilege permissions, secure privileged-access pathways, session controls, and comprehensive audit trails.

• Adapt engineering tools and workflows to support secure, controlled access to production environments.

• Improve CI/CD and software supply chain security through secure builds, dependency and container scanning, provenance, artifact signing, software bills of materials (SBOMs), and policy enforcement.

• Develop practical security automation and platform guardrails that engineering teams can adopt, operate, and maintain.

• Collaborate directly with software engineers on technical design, prototyping, implementation, and the integration of security improvements into production systems.

• Contribute to broader security engineering initiatives, partnering with specialist teams when deeper domain expertise is required.

• Produce clear technical documentation, implementation guidance, and handover materials to support long-term ownership.

• Deliver changes through structured, low-risk implementation practices while preserving service availability and operational stability.

• Strong hands-on experience in Platform Engineering, DevOps, Site Reliability Engineering (SRE), DevSecOps, or Platform Security, supported by solid security fundamentals.

• Demonstrated experience designing and implementing security controls directly, rather than focusing solely on reviews, assessments, or reporting findings.

• Strong understanding of CI/CD pipelines, modern software delivery practices, and integrating security into developer workflows.

• Good knowledge of software supply chain security, including dependency management, secure builds, provenance, artifact signing, and vulnerability management.

• Understanding of identity and access management (IAM), role-based access control (RBAC), and least-privilege principles.

• Practical experience with container security and working knowledge of Kubernetes.

• Ability to write automation, scripts, or security tooling in a programming language; Go or Python experience is useful, with a willingness to work in Go where required.

• Experience collaborating with engineers to deliver practical security enhancements in production environments.

• Strong communication, technical documentation, and problem-solving skills, with the ability to explain security decisions and work effectively across teams.

• Terraform or other Infrastructure as Code (IaC) tools.

• Public cloud platforms such as AWS or Google Cloud Platform (GCP).

• Security automation, policy-as-code, or automated policy enforcement.

• Container and runtime isolation, sandboxing, or related execution security controls.

• Securing AI agents or other AI-enabled engineering tools, including using large language models (LLMs) for security analysis or automation.

• Threat modelling and security design practices.

• Mutual TLS (mTLS), public key infrastructure (PKI), cryptography, or key management.

• Working in regulated industries, financial services, or other business-critical environments.

Relevant technical environment: Go, Python, CI/CD, Kubernetes, Terraform, AWS, GCP, IAM, RBAC, software supply chain security, security policy automation, and AI security controls.