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Unconventional AI

Analog computing substrate for energy-efficient AI

Member of Technical Staff - Cloud Infrastructure

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • A Bachelor of Science in Computer Science or equivalent practical experience.
  • At least 5 years of full-stack software engineering experience across frontend and backend development.
  • Strong programming proficiency in Python and/or modern JavaScript ecosystems, including Node.js, React, or Next.js.
  • Hands-on experience building agentic applications, including large language model orchestration with LangChain or similar frameworks.
  • Solid database fundamentals and practical experience using both standard SQL databases and vector databases.
  • Experience with DevOps practices, continuous integration and continuous delivery, and end-to-end operational ownership of application deployment.
  • An AI-native development workflow and comfort using AI coding assistants such as Cursor, Claude Code, or Codex.
  • A demoable portfolio of personal or past projects showcasing relevant full-stack or AI-driven builds.

Responsibilities

  • Architect, build, and maintain bespoke internal enterprise productivity applications powered by agentic AI, such as smart recruiting tools, contextual assistants, and semantic search.
  • Take full lifecycle ownership of applications and use the Databricks Apps platform to streamline deployment, hosting, and scaling while ensuring internal tools are reliable and performant.
  • Define what needs to be built, collaborate with internal stakeholders to gather requirements, rapidly prototype, collect feedback, and prioritize the roadmap.
  • Continuously evaluate the AI ecosystem and drive build-versus-buy decisions for internal tooling to solve problems with speed and efficiency.

Desired Qualifications

  • Experience in enterprise application development, particularly building internal productivity or operations tools.
  • Deep understanding of application security, including implementing authentication protocols such as SSO, OAuth, or SAML and robust access controls.
  • Expertise in designing and deploying robust retrieval-augmented generation pipelines and using advanced prompt-engineering techniques.
  • Hands-on experience deploying, scaling, and maintaining applications in major cloud environments such as AWS, GCP, or Azure.
  • Familiarity with machine learning or silicon engineering.

About the Company

Unconventional AI

Analog computing substrate for energy-efficient AI

Unconventional AI designs analog AI hardware and silicon substrates that run neural networks directly in hardware. Its chips use analog circuits that mimic biological neuron dynamics to process AI workloads in the physics of silicon, reducing energy use compared with digital GPUs. It differentiates itself by pursuing an in-hardware, neuromorphic-style substrate rather than optimizing existing GPUs, supported by prominent venture funding. Its goal is to counter the AI energy bottleneck and enable scalable AI in data centers with biology-scale efficiency.

Company size
51-200
Company stage
Seed
Total funding
$475M
Headquarters
San Diego, CA
Founded
2025

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