Remote AI Platform Engineer — Automate Engineering

cornelisnetworks; Austin (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

Cornelis Networks seeks an AI Platform Engineer to shape how engineering uses AI to design, validate, and support advanced networking products. You will build and grow a private AI platform with agents that automate engineering workflows, integrating with Linux-based services and enterprise tools.

The role emphasizes practical AI tooling, cost-aware decisions, and reliable, secure deployments to accelerate hardware/software development across CPUs, GPUs, and ASICs.

Qualifications

• B.S. or M.S. in Computer Science, Engineering, or a related discipline, or equivalent practical experience.
• Proficient in Python and software development fundamentals, with experience in Linux environments.
• Hands-on AI agent development, MCP/MCP-based workflows, RAG, and integration with tools.
• Experience building production-grade APIs, automation, and cost-aware engineering practices.

Responsibilities

• Own the AI Platform: configure tooling and infrastructure for a private domain-aware AI assistant for engineers.
• Design and grow autonomous agents that automate engineering operations and knowledge work.
• Develop FastAPI REST API, CLI, and chat integration; balance lightweight vs heavy models.
• Maintain containerized Linux services, proxies, timers; integrate with GitHub, Jira, Confluence, Teams.
• Build CI/CD validation pipelines and lead inner-source contributions; monitor platform costs.

Skills

Python programming

Linux

REST API

CI/CD

Shell scripting

Debugging

Education

B.S. or M.S. in Computer Science or Engineering

Tools

FastAPI

GitHub

Jira

Confluence

PostgreSQL

Redis

Docker/Podman

Job description

Cornelis Networks seeks an AI Platform Engineer to shape how engineering uses AI to design, validate, and support advanced networking products. You will build and grow a private AI platform with agents that automate engineering workflows, integrating with Linux-based services and enterprise tools.

The role emphasizes practical AI tooling, cost-aware decisions, and reliable, secure deployments to accelerate hardware/software development across CPUs, GPUs, and ASICs.