Senior DevOps / Platform Engineer – Autonomous Vulnerability Research (Harness Engineering)

Overview

In this role you will design, build and operate a Kubernetes-based platform for autonomous vulnerability research at scale, enabling secure, auditable AI-powered workloads. You will own IaC across GCP, implement hardened container/VM images, and enforce strict egress and segmentation to ensure safe research. You’ll collaborate with AI Engineering and Security Architecture to demonstrate control effectiveness, while accelerating researcher velocity within a security-first culture. This is a hands-on, platform-building role that drives secure, scalable research capabilities at Lloyds Banking Group.

Pay / Benefits

• up to 15% pension contribution
• annual performance-related bonus
• share schemes including free shares
• discounted shopping
• 30 days’ holiday plus bank holidays
• wellbeing initiatives and parental leave policies

Responsibilities

• Design, build, and operate the Kubernetes-based platform hosting agentic research workloads
• Own infrastructure-as-code across GCP using Terraform for reproducible environments
• Engineer secure container/VM images with hardened baselines and automated patching
• Implement egress-controlled networking, network policy, and segmentation for sanctioned targets
• Build CI/CD pipelines with integrated supply-chain security, including SBOMs and image signing
• Deliver observability across logs, metrics, traces, and cost telemetry for long-running workloads
• Create evidence-capture pipelines with immutable audit trails and run records
• Manage secrets, identity, and workload authentication with least-privilege access
• Collaborate with AI Engineering and Security Architecture to ensure safe, scalable runtimes

Key requirements

• Deep, hands-on Kubernetes experience (workload design, networking, autoscaling, RBAC, multi-tenancy)
• Strong Terraform and IaC skills with production cloud estates experience
• Substantial GCP experience (GKE, IAM, VPC/networking, Cloud Build/Artifact Registry) or equivalent cloud depth
• Container and VM hardening, including image minimisation and vulnerability management
• Experience implementing egress control, network policy, and segmentation in cloud-native environments
• Strong CI/CD engineering with security controls embedded into delivery pipelines
• Observability expertise across logging, tracing, and metrics with auditability
• Security-first mindset balancing researcher velocity with containment requirements
• Knowledge of artefact provenance and secure software supply chains
• Ability to operate in highly regulated environments or similar contexts
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• Security-minded decision making
• Collaborative, cross-functional teaming
• Judgement to balance speed with control
• Kubernetes
• Terraform
• GCP (GKE, IAM, VPC, Cloud Build, Artifact Registry)

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