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About the Role
As a Forward Deployed Engineer (FDE) with a Platform Engineering focus (Band 8), you will own end-to-end delivery for cloud platform and infrastructure modernizations, including the platform foundations that generative AI and agentic systems run on. You will translate business challenges into target-state cloud solutions, lead solution design and deployment, and work closely with AI engineers to ensure proper integration of platform and agentic AI workstreams. You will 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.
Responsibilities
- 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
Requirements
- 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
- 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
Skills
- Platform Engineering
- Cloud Platform Modernization
- Generative AI
- Agentic Systems
- Infrastructure as Code (IaC)
- Automation
- Solution Architecture
- Platform Architecture
- Azure
- GCP
- AWS
- Kubernetes
- GitOps
- ArgoCD
- Terraform
- Helm
- CI/CD
- SSL/TLS Certificate Lifecycle Management
- DNS Zone Management
- Network Security
- Policy-as-code
- Open Policy Agent (OPA)
- Access Controls
- Secrets Management
- Compliance-driven Engineering
- Observability
- Grafana
- Prometheus
- OpenTelemetry
- LLM Hosting
- LLM Gateways
- MLOps
- LLMOps
- Agentic AI Frameworks
- LangGraph
- CrewAI
- AutoGen
- Semantic Kernel
- LLM Governance
- Data Privacy
- Responsible-use Controls
- Legacy Application Modernization
- Containerization
- Microservices Re-platforming
- Technical Consulting
- Git
- GitHub
Location
- Customer Premises
Work Type
- Hybrid
Experience Level
- 5+ years
Education Level
- Degree in Computer Science, Software Engineering, Information Technology, or a related discipline — or equivalent professional experience
Benefits
- Be Well programs supporting financial, mental, physical, and social health
- Access to cutting-edge learning opportunities
- Certifications with Microsoft, Google, and Amazon
- Coaching
- Hands-on experiences
About the Company
- Kyndryl runs and reimagines 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.
- Kyndryl focuses on ensuring all Kyndryls feel included and welcomes people of all cultures, backgrounds, and experiences.
- Kyndryl's culture is built on kinship, empathy, and shared success.
Equal Opportunity
- Kyndryl welcomes people of all cultures, backgrounds, and experiences.
- We encourage you to apply even if you don’t meet every requirement.
- We believe in growth, and we’re excited to see what you can bring.
- Kyndryl gives you the ability to thrive and contribute to our culture of empathy and shared success.