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Forward Deployed Engineer - Lead Platform Engineer

Job in Plymouth, Devon, PL2, England, UK
Listing for: 3620 Kyndryl Uk Limited
Full Time position
Listed on 2026-10-31
Job specializations:
  • IT/Tech
    Systems Engineer, Cloud Computing: Infrastructure & Operations
Salary/Wage Range or Industry Benchmark: 110000 - 150000 GBP Yearly GBP 110000.00 150000.00 YEAR
Job Description & How to Apply Below
Who We Are

At Kyndryl, we run and reimagine the mission-critical technology systems that drive advantage for the world’s leading businesses. We are at the heart of progress; with proven expertise and a continuous flow of AI-powered insight, enabling smarter decisions, faster innovation, and a lasting competitive edge. For our people—Kyndryls—that means doing purposeful work that powers human progress. Join us and experience a flexible, supportive environment where your well-being is prioritized and your potential can thrive.

The Role Your Role

As a Forward Deployed Lead / Principal Engineer (FDE) with a Platform Engineering focus (Band
9), you own architectural direction and delivery for major digital transformation programmes, including the platforms that power generative AI and agentic systems. You align enterprise goals with target-state cloud architectures, guide theteam’s technical direction while staying close to the work, and partner closely with the AI engineers on the team.

You combine deep expertise in cloud platforms and enterprise architecture with strong consulting acumen. You establish architectural governance, champion Infrastructure as Code (IaC) and automation, andact as a go-to technical reference on complex engagements.

What You Will Do
  • Design and build target-state cloud platforms across Azure, GCP, andAWS
  • Establish enterprise container platforms (Kubernetes) and Git Ops-based delivery (ArgoCD)
  • Build self-service developer frameworks and landing zones, hands-onwith Terraform and Helm
  • Architect platforms that host and serve generative AI systems (LLMhosting, LLM gateways, agentic workflows)
  • Guide legacy application modernisation, microservices migrations, andAPI 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 zonesand the hyperscaler
  • Own connectivity and network-level security: SSL/TLS certificatelifecycle management, DNS zone management, and secure network accessto endpoints
  • Define architectural standards and guardrails, with security as afirst-class concern (policy-as-code / OPA, access controls, secrets management, compliance-driven engineering)
  • Instrument platforms for observability (Grafana, Prometheus,Open Telemetry)
  • Provide architectural oversight across multi-disciplinary work streams,staying close enough to unblock the team directly
  • Capture field learnings, codify reusable patterns and blueprints, andmentor engineers hands-on
  • Translate enterprise requirements into technical roadmaps for senior stakeholders
Who You Are Job Qualifications Required Skills and Experience
  • 8–10+ years in enterprise or platform architecture, leading client-facing platform transformations
  • Deep, hands-on expertise across Azure, GCP, and AWS (landing zones,networking, IAM, cost and governance controls)
  • Strong command of Kubernetes, Git Ops 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, andsecure access in landing zones and the hyperscaler
  • Hands-on experience with SSL/TLS certificate management, DNS zone administration, and secure network access to endpoints
  • Hands-on experience with CI/CD pipelines, Git-based workflows, and microservices/API architectures
  • Practical experience with observability stacks (Grafana, Prometheus,Open Telemetry)
  • Experience with 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
  • Strong stakeholder communication, translating architecture into business outcomes for senior…
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