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AI Engineer

Job in San Jose, Santa Clara County, California, 95199, USA
Listing for: Spectro Cloud
Full Time position
Listed on 2026-09-12
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Cloud Computing: Infrastructure & Operations, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 160000 - 192000 USD Yearly USD 160000.00 192000.00 YEAR
Job Description & How to Apply Below

Who We Are

Spectro Cloud is the Kubernetes and AI infrastructure platform behind some of the most demanding AI environments in the world. Our PaletteAI platform, AI Inference Launchpad, and Instinct Coder solutions let operators stand up production-grade AI clusters - training, fine tuning, and inference - on any GPU, in any data center, at any scale. Neo Clouds and specialty GPU cloud providers are one of the fastest-growing segments in the AI economy, and Spectro Cloud is the platform layer they trust to bring differentiated, multi-tenant, GPU-native services to market.

About

the Job

As an AI engineer, you will be part of internal efforts to advance AI adoption across the company. You will design, build, and maintain internally focused solutions that help promote agentic workflows and automations that improve employee productivity.

This role will require you to wear different hats; one moment you are building a technical solution, and the next you may be engaging with risk, compliance, and legal to help define guardrails for a product or tool rollout. You will lead proof-of-concept initiatives, engage with employees during AI Office Hours to provide advice, and work with our internal partners to establish AI processes and guardrails.

You must be comfortable teaching and explaining ideas to non-technical audiences.

You are expected to have experience with various AI/ML workflows and AI development practices, primarily to advise, but also to shape the future of our products. We are an infrastructure-focused software company, so you are expected to have a strong understanding of infrastructure, spanning cloud and bare-metal environments. You should be comfortable creating automation solutions, with and without AI, that help us promote effective AI usage within the company.

Experience deploying and managing applications in production will help you propose and build sustainable solutions.

We are seeking self-starters eager to help shape the future of this new team. We're looking for someone who isn't afraid to share recommendations and guidance on AI initiatives and AI adoption within an organization. We face several unknowns that we must tackle together. If you enjoy working in a highly technical environment with autonomy, at a rapid pace, and with regular challenges, then this role is right for you.

Minimum Qualifications
  • Bachelor's Degree or an Advanced Degree in Computer Science, Information Technology, or a similar field.
  • 4+ years of experience as a Software Engineer, SRE, ML Engineer, Solutions Architect, or similar technical role is required
  • 4+ years of experience maintaining and building production applications.
  • Possesses a broad knowledge and experience across AI topics, including agent based systems, model tuning, model deployment, MCP server development, and more.
  • Highly proficient with at least one of the following programming languages:
    Python, Go, or JavaScript/Type Script (We prefer Go)
  • Experience with application testing and continuous integration/continuous delivery (CI/CD). This will come into play as you build and maintain solutions the AI team will own and support.
  • Project management experience. You are capable of leading and driving projects, such as proof-of-concept and the rollout of a new technical solution organization-wide.
  • Excellent communication skills, both written and oral. You will be expected to participate and lead office hours. You must be able to articulate technical concepts to engineers, non-engineers, and executives.
  • Experience with Infrastructure as Code, preferably Terraform.
  • Experience with public cloud providers (AWS, Azure, GCP, Oracle), and on-prem infrastructure.
  • Deep understanding of containers and how container orchestration systems work, such as…
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