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Omen AI

Real-time fluid analysis for machinery health

GTM Wizard

Full-Stack EngineeringConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USANo salary listed

About the Job

Requirements

  • Daily use of AI coding agents and ability to structure codebases, context files, and task handoffs so agents produce correct work and to identify when their output is wrong.
  • A software foundation demonstrated by a computer science degree, a bootcamp, or substantial self-built projects; ability to read and debug generated code and understand data models.
  • Ability to solve ambiguous business problems with working solutions.
  • Ability to communicate clearly with non-engineers.
  • No minimum years of experience are required.
  • Experience with TypeScript, Next.js, Python, Postgres (Supabase), Vercel, or third-party APIs is a plus; ability to learn whichever tools a problem requires.

Responsibilities

  • Build and ship features across internal platforms, including CRM, FP&A models, and customer success, from specification to production, often within the same week; take ownership of delivered work.
  • Work with the Operations lead to automate inventory, procurement, deployment, and field-operations workflows.
  • Maintain clean, trustworthy pipeline data and integrate new tools adopted by the sales team.
  • Connect services through their APIs and build synchronization jobs that handle rate limits and failures without losing data.
  • Use and extend the agent setup, including Claude Code, Codex, skills, MCP servers, and scheduled agents, to increase per-person productivity.

Desired Qualifications

  • Include links to things built, such as a GitHub profile, deployed app, internal tool, automation, or a short recording demonstrating an agent workflow; side projects count, and a strong portfolio is valued over a strong resume.

About the Company

Omen AI

Real-time fluid analysis for machinery health

Omen AI provides a continuous fluid intelligence platform that monitors the health of liquids inside machinery in real time to prevent costly failures. It uses spectroscopic sensors installed in machines to track 21+ elemental signatures in fluids like oil, coolant, and water, including wear metals, bio-contaminants, and degradation indicators. The system supports both a permanent, non-invasive sensor for single-machine monitoring and a portable diagnostic unit for on-site checks across multiple assets, eliminating the need for slow off-site lab tests. Its goal is to reduce unplanned downtime for data centers and industrial operators and to scale manufacturing and product engineering after its Series A funding.

Company size
11-50
Company stage
Series A
Total funding
$31M
Headquarters
San Francisco, CA
Founded
2024

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