Senior Platform Engineer, AI Infrastructure
About The Position
Focused is hiring a Senior Platform Engineer to lead the build-out of an enterprise AI platform for a global enterprise client. The role will establish the foundation client teams use to build and deploy LLM applications and agents, including Kubernetes, GPU capacity, security, and governance guardrails. The engineer will set technical direction and mentor a Platform Engineer working on the engagement. The position combines AI platform architecture, cloud and Kubernetes infrastructure, security and governance, and client-facing technical leadership. The engineer will make architecture and build-versus-buy decisions, guide implementation, and help the client's engineering team take over and operate the resulting platform.
Requirements
- 10+ years of experience in infrastructure, platform, or DevOps engineering.
- Deep production experience with Kubernetes, including Azure AKS.
- Hands-on experience with GCP.
- Expert-level Terraform skills.
- Experience running GPU infrastructure, such as NVIDIA GPU Operator, node pools, or workload scheduling.
- Experience building infrastructure that supports LLM workloads in production.
- Strong cloud security background, including IAM, networking, secrets, and policy as code.
- Experience leading technical direction for a team.
Nice To Haves
- Experience building an internal agentic AI platform.
- Familiarity with model serving technologies such as vLLM, Triton, KServe, or Ray Serve.
- Experience with Azure OpenAI or Vertex AI.
- Consulting or client-facing experience.
Responsibilities
- Design and build a multi-tenant platform for LLM and agentic AI workloads, from model access through deployment.
- Architect GPU infrastructure for inference and fine-tuning, including scheduling, autoscaling, and cost controls.
- Establish shared agent services, including model gateways, secrets, tracing, evaluation, and deployment pipelines.
- Make build-versus-buy decisions and explain tradeoffs to technical and executive stakeholders.
- Architect and operate production Kubernetes on Azure AKS and GCP GKE.
- Own Terraform modules and infrastructure-as-code standards across environments.
- Build CI/CD and GitOps workflows that make platform changes safe and repeatable.
- Design identity, network isolation, and secrets management for AI workloads.
- Establish guardrails for data access, model usage, and auditability.
- Partner with security and compliance teams to meet enterprise requirements.
- Mentor and direct a Platform Engineer on the engagement.
- Lead architecture reviews and write decision records.
- Build trust with client engineering leaders and leave the client team able to run the platform.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
