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 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
Who You Are
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…