Member of Technical Staff [Product]

NeoCognitionPalo Alto, CA

About The Position

As a Member of Technical Staff [Product] at NeoCognition, you’ll be one of the founding engineers transforming our research into real, user-facing products and developer experiences. You’ll work across the full stack — from backend APIs and data infrastructure to front-end interfaces and SDKs — to make our large language model (LLM) agent research usable and impactful. This role blends product engineering with systems thinking: you’ll build not only applications but also the developer tools and libraries that make those applications scalable, reliable, and delightful to use. You’ll collaborate closely with research scientists, platform engineers, and UX researchers to define, build, and ship the next generation of AI-powered products and developer experiences.

Requirements

  • Proven experience in shipping and maintaining full-cycle software products — from prototype to production to iteration.
  • Strong programming skills in Python, TypeScript/JavaScript, or equivalent, with experience in modern web frameworks (e.g., React, Next.js, FastAPI, Flask).
  • Solid understanding of application architecture, scaling, and reliability in a cloud environment (AWS, GCP, or equivalent).
  • Experience building developer tools, SDKs, or shared libraries used by other engineers or external developers.
  • Ability to thrive in a fast-moving, early-stage environment with high autonomy and cross-functional collaboration.

Nice To Haves

  • Experience integrating AI or LLM-based features into production applications.
  • Familiarity with API design and developer experience (DX) best practices.
  • Background in open-source contributions or building platforms others depend on.
  • Interest in product design, usability, and the end-user experience of developer tools.

Responsibilities

  • Design, build, and maintain production-ready applications and developer tools, including web apps, APIs, SDKs, and internal libraries.
  • Drive the end-to-end product lifecycle — from concept and prototype to launch, iteration, and user feedback.
  • Translate cutting-edge research outputs into robust, usable product features and developer-facing abstractions.
  • Contribute to the architecture, design, and scalability of systems as usage grows.
  • Collaborate across research, design, and infrastructure teams to align product goals with technical feasibility.
  • Define and uphold engineering excellence — testing, CI/CD, documentation, and deployment best practices.
  • Build tools and abstractions that make it easier for both internal teams and external developers to leverage our AI systems.
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