AI Platform Engineer

🔥 9 minutes ago

🤠 Texas – Remote

🤠 Texas – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🏗️ Platform Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Cornelis Networks

WebsiteLinkedInAll Job Openings

51 - 200 employees

🤖 Artificial Intelligence

🔧 Hardware

🏢 Enterprise

💰 $29M Series B on 2022-11

Artificial Intelligence • Hardware • Enterprise

Cornelis Networks is a leading provider of intelligent, scalable, high-performance interconnects designed for AI applications. The company specializes in delivering end-to-end purpose-built high-performance fabrics to commercial, scientific, academic, and government organizations. Cornelis Networks’ solutions are aimed at enhancing performance, scalability, and efficiency across hyperscale, cloud AI, and on-premises AI/HPC environments. Their offerings are known for scalable architecture, high bandwidth solutions, and universal compatibility with accelerators and GPUs. Originating as an Intel spin-off, the company is positioned to challenge existing technologies like InfiniBand and Ethernet, providing advanced interconnects that power modern AI infrastructure.

📋 Description

• Own the AI Platform: Own the configuration, tooling, and infrastructure that gives every Cornelis engineer a private, domain-aware AI assistant. Keep it current, reliable, and tuned to the specific technical domains our engineers work in - not generic web development tasks, but low-level systems work: drivers, firmware, ASIC register maps, hardware/software integration. • Build Out the Agent Workforce: Design, implement, and improve a growing workforce of autonomous agents that automate engineering operations. Each new agent you build becomes a permanent part of how the engineering organization operates. The backlog of planned agents is substantial and the opportunity to shape what gets built and how is real. • Design and Implement New Agents: Take agents from concept to production: FastAPI REST API, CLI interface, and chat integration. Work with engineering teams to identify the highest-value automation opportunities, define the agent's behavior, and build it to the platform's standards - deterministic where possible, LLM-powered where it adds real value, and cost-conscious throughout. • Maintain and Improve the Infrastructure: Keep the platform running reliably: containerized services on Linux, reverse proxies, systemd timers, PostgreSQL and Redis, secrets management, and enterprise integrations with GitHub, Jira, Confluence, and Microsoft Teams. • Write and Improve Agent Skills and Prompt Engineering: Author and tune the structured workflows and system instructions that make AI agents useful for deep engineering work. Design agents that are reliable and grounded - not impressive in a demo but wrong in production. • Build CI/CD Validation Pipelines: Build and maintain automated validation that catches bad configurations, leaked credentials, and broken agent contracts before they land. • Manage Cost and Value Across the Platform: Track what the platform costs and what it delivers. Make deliberate decisions about model selection, token usage, and when AI is the right tool versus when deterministic code is cheaper and more reliable. • Track the AI Landscape and Keep the Platform Current: Evaluate what matters, adopt what improves the platform, and upgrade before the team falls behind.

🎯 Requirements

• B.S. or M.S. in Computer Science, Engineering, or a related discipline, or equivalent practical experience • Python or Equivalent Programming Language: Experience building software, applications, scripts, or services in Python or a comparable general-purpose programming language, with the ability and willingness to work in Python • Familiarity with software development fundamentals, including version control, testing, debugging, and code review • Practical experience developing, deploying, operating, or troubleshooting software in a Linux environment • Hands-on experience implementing, integrating, extending, or operating MCP clients, servers, tools, or MCP-based workflows • Ability to explain how MCP was used to connect an AI system to tools or external systems • Hands-on experience building an AI agent or LLM-powered workflow that performs meaningful work using tools, APIs, structured workflows, files, databases, or external systems • Experience building or integrating a RAG workflow that grounds model output in documentation, code, databases, files, or other authoritative information

🏖️ Benefits

• health and retirement benefits • equity, cash, and incentives • medical, dental, and vision coverage • disability and life insurance • dependent care flexible spending account • accidental injury insurance • pet insurance • generous paid holidays • 401(k) with company match • Open Time Off (OTO) for regular full-time exempt employees • other paid time off benefits include sick time, bonding leave, and pregnancy disability leave