Lead AI Infrastructure Engineer: Kubernetes & GPU

Seekr; Washington (District of Columbia); Hybrid; USD 180,000 - 230,000; Full time

Benefits offered by this job

Equity ownership

Unlimited PTO

Hybrid work (Reston, VA & Austin, TX)

Job summary

Seekr is hiring a Staff AI Infrastructure Engineer to design, build, and operate the platforms enabling large‑scale training, serving, evaluation, and deployment of foundation models and autonomous AI agents.

You will work across distributed systems, Kubernetes, GPU infrastructure, and enterprise AI platforms to deliver secure, scalable, and reliable systems that span edge to trillion‑parameter models. This role requires deep expertise in cloud‑native infra and production software.

Qualifications

• 8–12+ years in distributed systems or large-scale platforms.
• Experience designing and operating production Kubernetes environments.
• Strong Python and systems programming skills.

Responsibilities

• Design, build, and maintain production AI infrastructure for training, inference, evaluation, and deployment.
• Operate scalable Kubernetes-based infrastructure for GPU workloads across cloud, on-premises, hybrid, and edge environments.
• Lead architecture discussions, mentor engineers, and drive engineering standards across the AI Infrastructure team.
• Troubleshoot complex distributed systems and drive continuous operational improvement.

Skills

Distributed systems

Kubernetes

Python

Go/Rust/C++

AI infrastructure

Cloud platforms

CI/CD

GitOps

IaC

Education

Bachelor's degree or higher

Tools

Prometheus

Grafana

OpenTelemetry

Docker

Kubernetes tooling

Job description

Seekr is hiring a Staff AI Infrastructure Engineer to design, build, and operate the platforms enabling large‑scale training, serving, evaluation, and deployment of foundation models and autonomous AI agents.

You will work across distributed systems, Kubernetes, GPU infrastructure, and enterprise AI platforms to deliver secure, scalable, and reliable systems that span edge to trillion‑parameter models. This role requires deep expertise in cloud‑native infra and production software.