Forward Deployed Engineer - Lead Platform Engineer

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 the team'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, and act as a go-to technical reference on complex engagements.

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.

• Design and build target-state cloud platforms across Azure, GCP, and AWS

• Establish enterprise container platforms (Kubernetes) and GitOps-based delivery (ArgoCD)

• Build self-service developer frameworks and landing zones, hands-on with Terraform and Helm

• Architect platforms that host and serve generative AI systems (LLM hosting, LLM gateways, agentic workflows)

• 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)

• Provide architectural oversight across multi-disciplinary workstreams, staying close enough to unblock the team directly

• Capture field learnings, codify reusable patterns and blueprints, and mentor engineers hands-on

• Translate enterprise requirements into technical roadmaps for senior stakeholders

• 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, 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

• Hands-on experience with CI/CD pipelines, Git-based workflows, and microservices/API architectures

• Practical experience with observability stacks (Grafana, Prometheus, OpenTelemetry)

• 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 stakeholders

• 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

• Track record defining and enforcing architectural governance, security standards, and risk frameworks

• T-shaped profile: deep expertise in platform engineering and cloud architecture, broad understanding across software engineering, security, and consulting

• 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