Job Description

Job Summary

Hands-on cloud-native platform engineer responsible for building and maintaining the runtime, tooling, and integration plumbing that powers the AI Force AI Workbench and client modernization environments. This role keeps the GenAI-enabled modernization factory running — provisioning sandboxes, integrating MCP servers, and ensuring secure prompt delivery against client codebases

Key Responsibilities

Build and maintain Kubernetes-based environments (EKS, AKS, GKE, OpenShift, or Rancher) that host AI Force AI Workbench components.

Configure and operate MCP servers that connect LLMs to client source repositories, ticketing systems, and documentation stores.

Implement infrastructure-as-code (Terraform, Bicep, Pulumi) for repeatable client landing zones.

Integrate multi-model LLM endpoints (Claude, GPT, Gemini, Llama, Nemotron) with secure prompt routing and guardrails.

Support reverse-engineering runs against legacy codebases by preparing ingestion pipelines and embedding stores.

Support AI Led application refactoring, re-platforming and re-write for legacy modernization

Participate in on-call rotation for the CNCoE shared platform.

Skill Requirements

2–4 years building and operating production cloud infrastructure on AWS, Azure, or GCP.

Hands on skills on Prompt engineering, Langchain, LangGraph and Agentic application development

Proficiency in Code Assist tools like MS Co-pilot, Claude and Codex

Working knowledge of Kubernetes, containers, and Helm.

Proficiency in at least one IaC tool (Terraform strongly preferred) and DevSecOps tools

Scripting in PowerShell Python, Bash, or Go.

Understanding of identity, secrets management, and network segmentation in cloud environments.

Proficiency in .Net or Java application development and modernization

Proficiency in database concepts and database configurations

Other Requirements

Experience integrating LLM APIs or building RAG pipelines.

Familiarity with the Model Context Protocol (MCP) or agent frameworks.

Associate-level cloud certification (AWS SAA, AZ-104, GCP ACE).

GTM & Evangelism Contribution

Spins up demo environments and reference architectures used in client pursuits and conference demos.