Adapt

Full Stack Engineer (Remote)

About Adapt

Adapt is the AI brain of your business. It unifies every data source—databases, SaaS tools, support tickets, documents, and more—into a single conversational interface that delivers the highest level of intelligence the AI industry has to offer. Our autonomous agents continuously monitor KPIs, surface anomalies, diagnose root causes, and recommend next steps so organizations can act decisively. We serve startups and SMBs looking to move from endless dashboards and noisy AI to evidence-backed insight and action.


About the role

As Adapt’s Front-end Developer, you’ll own the look, feel, and performance of our web and embedded chat interfaces. You’ll translate product requirements into polished, responsive user experiences that let business leaders and analysts interact intuitively with AI-driven insights.


What you'll do

  • Develop an agent runtime for orchestrating multi-agent pipelines for data integration and analysis.
  • Implement server-side logic and APIs with Node to power core product features.
  • Build secure and scalable container sandboxes for code execution.
  • Implement context management systems built on object storage and vector databases such as pgvector.
  • Build interactive and rich frontend interfaces using Tailwind and Next.js.
  • Work closely with product, design, and AI researchers to prototype and launch new features.

Qualifications

  • 5+ years of experience building large scale systems and platforms.
  • Experience working with containers, container runtimes, and virtualization. Comfortable working with container orchestration systems such as Kubernetes.
  • Strong Typescript/Node background and a language-agnostic approach to problem solving.

Nice-to-Haves

  • Exposure to AI/ML APIs or productionizing ML systems.
  • Familiarity model and agent evaluations.
  • Knowledge of security best-practices for containerized execution of untrusted code.

The pay range for this role is:

200,000 - 250,000 USD per year (San Francisco, California)

R&D

Remote (United States)

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