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Fullstack/AI Engineer

Poka Labs· Engineering
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Hybrid (San Francisco, CA)$120k - $170k + equityFull-timePosted 2mo ago

About the role

Role focused on building and scaling production AI agents and full-stack features for quotes, pricing, and related workflows in the industrial manufacturing sector.

Responsibilities

  • Core product features from frontend to backend.
  • Infrastructure that keeps agents reliable in real environments.
  • Customer understanding through direct exposure to plants and operations.
  • Evaluation and deployment of new AI capabilities.

Qualifications

  • Strong full stack ability. You’ll be part UI designer, product manager, data engineer, and prompt whisperer.
  • Willingness to dig into the weeds when needed, but able to let AI handle straightforward tasks.
  • Ability to clearly explain a complicated system to both technical and non-technical audiences.
  • Based in San Francisco or willing to relocate.

Skills

Required:Full stack developmentFrontend frameworks (TypeScript, Next, React)AI / LLM integrationCommunication

Benefits

  • True ownership over the core architecture and product.
  • Immediate impact inside global manufacturing environments.
  • A role in shaping our culture and traditions. Include an absurd addition in your application (optional).
  • Direct collaboration with founders who have deep domain experience.
Last updated Sep 23, 2026. Interested? Apply on the company site.
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About Poka Labs

The modern operating system for chemical manufacturing.

Poka Labs is developing an AI platform to automate operations tasks in chemical manufacturing, beginning with production scheduling. Traditionally, these tasks are performed manually using spreadsheets. Our software seamlessly integrates with existing data sources such as data historians, emails, and PDFs to automate analytics, scheduling, changes, and communication within a single platform. Malay and Andrew met while pursuing their MBAs at Harvard Business School. Malay previously worked as an engineer in the specialty chemical industry, saving his employers over $100 million across US, China, and German plants. Andrew worked as a software engineer on data infrastructure at Meta and optimization problems at a seed-stage startup. He also completed a Masters degree at Harvard specializing in Machine Learning.

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