Platform Engineer, AI Infrastructure

About the role

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 Platform Engineer to help build an enterprise AI platform for a global enterprise client. You'll work alongside a Senior Platform Engineer on the Kubernetes and cloud foundation, and you'll also get hands-on with the AI side: wiring up model access, deploying agents, and helping application teams get their LLM workloads into production. If you like infrastructure but want to build with AI too, this role is for you.

Key Responsibilities:

Platform & Infrastructure

- Build and operate Kubernetes clusters on Azure AKS and GCP GKE

- Write and maintain Terraform modules for cloud resources and environments

- Build CI/CD and GitOps pipelines for platform and application deployments

- Monitor, troubleshoot, and improve the reliability of AI/ML platform services

AI Platform Engineering & Operations

- Deploy and operate supporting services for LLM applications: model gateways, vector databases, tracing, and evaluation

- Support GPU workloads, including node pools, scheduling, and cost monitoring

- Write runbooks and automate day-two operations

AI Engineering

- Build reference agents and LLM application templates that client teams can start from

- Help application teams integrate with the platform and debug their workloads

- Prototype with agent frameworks and LLM APIs to test what the platform needs to support

Required Qualifications:

- 5+ years in platform, infrastructure, DevOps, or SRE roles

- Hands-on production experience with Kubernetes

- Experience with Azure and/or GCP

- Experience with Terraform or similar IaC tools

- Experience supporting AI/ML platforms or ML workloads in production

- Proficiency in Python plus solid scripting skills

Preferred Qualifications (Exceptional Candidates):