As a Forward Deployed Engineer (FDE) with a Platform Engineering focus (Band 8), you own end-to-end delivery for cloud platform and infrastructure modernisations, including the platform foundations that generative AI and agentic systems run on. You translate business challenges into target-state cloud solutions, lead solution design and deployment, and work closely with the AI engineers on the team to keep platform and agentic AI workstreams properly integrated.
You operate with significant autonomy, bring deep technical expertise in solution and platform architecture, and use Infrastructure as Code (IaC) and modern automation across the full delivery lifecycle to accelerate deployment, improve reliability, and deliver measurable impact.
What You Will Do
Depending on the engagement, you’ll draw on some of the below more than others — not every bullet applies to every project.
- Translate business challenges into target-state cloud platforms across Azure, GCP, and AWS
- Build enterprise container platforms (Kubernetes) and GitOps-based delivery (ArgoCD)
- Build self-service developer environments and secure landing zones
- Support platforms that host and serve generative AI systems (LLM hosting, LLM gateways, agentic workflows)
- Own delivery end-to-end: build CI/CD pipelines and implement Infrastructure as Code (Terraform, Helm)
- Guide legacy application modernisation, microservices migrations, and API integrations
- Implement security end-to-end across the platform: security tooling built into CI/CD pipelines, namespace segmentation and managed identities in Kubernetes, and secure access controls in landing zones and the hyperscaler
- Own connectivity and network-level security: SSL/TLS certificate lifecycle management, DNS zone management, and secure network access to endpoints
- Define architectural standards and guardrails, with security as a first-class concern (policy-as-code / OPA, access controls, secrets management, compliance-driven engineering)
- Instrument platforms for observability (Grafana, Prometheus, OpenTelemetry)
- Capture deployment learnings and share best practices to inform core platform frameworks
- Contribute code, automated blueprints, and feedback to core platform teams
Job Qualifications
You don’t need to tick every box below to apply — this reflects the breadth of the role, not a strict checklist.
Required Skills and Experience
- 5+ years of hands‑on experience in solution and platform architecture, delivering client‑facing infrastructure modernisations
- Hands‑on expertise with Azure, GCP, and/or AWS (landing zones, networking, IAM, cost controls)
- Production experience with Kubernetes, GitOps delivery (ArgoCD), and Infrastructure as Code (Terraform, Helm)
- Hands‑on experience implementing security end‑to‑end: CI/CD security tooling, Kubernetes namespace segmentation and managed identities, and secure access in landing zones and the hyperscaler
- Hands‑on experience with SSL/TLS certificate management, DNS zone administration, and secure network access to endpoints
- Solid grasp of CI/CD pipelines, version control (Git & GitHub), and microservices/API architectures
- Practical experience with observability tooling (Grafana, Prometheus, OpenTelemetry)
- Working knowledge of generative AI platforms: LLM hosting, LLM gateways (e.g. LiteLLM, Portkey, Kong AI Gateway), and MLOps/LLMOps practices for deploying and monitoring AI systems in production
Preferred Skills and Experience
- Familiarity with agentic AI frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel) and their production deployment
- Understanding of LLM governance: data privacy, guardrails, and responsible‑use controls
- Experience guiding clients through legacy application modernisations, containerisation, and microservices re‑platforming
- Experience defining platform architectural guardrails and risk frameworks that balance delivery velocity with governance
- T‑shaped profile: solid technical expertise in platform engineering and cloud architecture, broad understanding across enterprise IT and technical consulting
- Ability to serve as a trusted advisor, translating business requirements into technical roadmaps for diverse stakeholders
- Willingness to travel and work on customer premises as required
- Degree in Computer Science, Software Engineering, Information Technology, or a related discipline - or equivalent professional experience
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