Senior Platform Engineer, AI Infrastructure

Who we are: At Focused, we move quickly to deliver quality software that achieves client outcomes and meets their customer's needs. We strategically partner with our clients to leverage our expertise in design and software, while our clients bring their own domain expertise. We work with a variety of clients from different industries, collaborating as we get new products to market, modernizing legacy systems, or helping teams learn the skills they need to be successful. Our values: • Listen first • We are experts in product practices but lifelong learners in the domain of our customers. We research, collaborate, and understand. • Learn why • We ask questions and talk to users to understand problem spaces, objectives, and goals, which allows us to deeply invest and drive towards the outcomes of our clients. • Love your craft • We love diving into a variety of domains and solving problems. We take pride in delivering value, in communicating progress, and guiding our clients to success. We're looking for a Senior Platform Engineer to lead the build-out of an enterprise AI platform for a global enterprise client. You'll design the foundation their teams use to ship LLM applications and agents: Kubernetes, GPU capacity, security, and the guardrails that let hundreds of engineers move fast without breaking things. You'll set technical direction and mentor a Platform Engineer working alongside you. Key Responsibilities: AI Platform Architecture • Design and build a multi-tenant platform for LLM and agentic AI workloads, from model access to deployment • Architect GPU infrastructure for inference and fine-tuning, including scheduling, autoscaling, and cost controls • Stand up shared services for agents: model gateways, secrets, tracing, evaluation, and deployment pipelines • Make build-vs-buy calls and explain the tradeoffs to technical and executive stakeholders Kubernetes & Cloud Infrastructure • Architect and run production Kubernetes on Azure AKS and GCP GKE • Own Terraform modules and IaC standards across environments • Build CI/CD and GitOps workflows that make platform changes safe and repeatable Security & Governance • Design identity, network isolation, and secrets management for AI workloads • Put guardrails in place for data access, model usage, and auditability • Partner with security and compliance teams to meet enterprise requirements Leadership & Consulting • Mentor and direct a Platform Engineer on the engagement • Lead architecture reviews and write the decision records that outlast the engagement • Build trust with client engineering leaders and leave their team able to run what we build Required Qualifications: • 10+ years in infrastructure, platform, or DevOps engineering • Deep production experience with Kubernetes, including Azure AKS • Hands-on experience with GCP • Expert-level Terraform • Experience running GPU infrastructure (NVIDIA GPU Operator, node pools, scheduling, or similar) • Experience building infrastructure that supports LLM workloads in production • Strong cloud security background: IAM, networking, secrets, policy as code • Experience leading technical direction for a team Preferred Qualifications (Exceptional Candidates): • Experience building an internal agentic AI platform • Familiarity with model serving (vLLM, Triton, KServe, Ray Serve) • Experience with Azure OpenAI or Vertex AI • Consulting or client-facing experience What Sets Exceptional Candidates Apart: • You've built a platform other engineering teams chose to adopt • You've cut GPU spend meaningfully without slowing teams down • You can explain a platform architecture to a CTO and a junior engineer in the same meeting What to know before you apply: • This role will require being in the Chicago