San Diego, California | San Mateo, California

Staff, Platform Engineer AI Compute (6034)

Salary: unknownOn-siteDevOps / SRE / platform / cloud

GolangPythonKubernetesTerraformLinuxPyTorch

Original posting ↗Apply ↗Company job board ↗See this job in Telegram

Shield AI, a company in aerospace and defense, has an open position for Staff, Platform Engineer AI Compute (6034). The role is on-site in San Diego, United States. We classify it under DevOps / SRE / platform / cloud. The stack in the posting includes Kubernetes, Terraform, Linux, PyTorch, Golang and Python. Perks named in the posting: equity. Shield AI has 147 open positions on this site, 61 of them in IT and engineering.

Posted today · Last checked 2026-11-03

About Shield AI

Aerospace and defense Non-tech company with an IT team 147 open positions, 41% in IT and engineering. Most open roles: Non-software engineering and technicians (46), Software engineering (general) (37), General management and executives (11).

All open jobs at Shield AI →

Similar jobs

Site Reliability EngineerPlanet · San Francisco, CAUSD 144.5K–180.6K / year Senior Systems Engineer, BizTechAirbnb · United StatesUSD 164K–193K / year Oracle E-Business Suite Solution Architect — Fit-Gap Discovery LeadTessera Labs · Remote in the U.S.USD 200K–225K / year System EngineerExegy · St. LouisHybrid Database AdministratorSteerBridge · Cherry Point, NCOn-site Oracle Financials Solution Architect-Finance to Manage (EBS and Fusion)Tessera Labs · Remote in the U.S.USD 200K–230K / year Sr. DevOps Engineer BusPatrol · TX - AustinHybrid Staff Network Engineer (AI Infrastructure) vCluster Labs · United States | CanadaUSD 170K–210K / year

1,400 open DevOps / SRE / platform / cloud jobs in the United States All open jobs at Shield AI →

Workplace	On-site
Seniority	Not stated
Role	DevOps / SRE / platform / cloud
Countries	United States
Languages	GolangPython
Employment type	Full Time Employee
Key facts	Stack: Golang, Python, Kubernetes, Terraform, Linux, PyTorch · Equity

The full description is on the original posting. Labels are set automatically and can be wrong. About the data