Founding Engineer

Posted 7 Days Ago
Hiring Remotely in San Francisco, CA, USA
Remote or Hybrid
100K-150K Annually
Entry level
Artificial Intelligence • Machine Learning • Software
The Role
Architect and build the company’s core data and AI infrastructure, including data pipelines, agentic workflows, backend systems, API integrations, frontend widgets, and developer tools. Own product verticals end to end, rapidly ship production-ready features, collaborate with founders on product direction, and help establish engineering culture, hiring, and development practices.
Summary Generated by Built In
We are an early-stage, fast-moving team building the next generation of data and AI infrastructure. Backed by top-tier venture capital, we are solving high-stakes, complex enterprise challenges by shifting traditional paradigms. We move fast, value extreme ownership, and prioritize shipping exceptional software over rigid processes.
As a Founding Engineer, you won’t just be writing code—you will be architecting our core platform from scratch, defining our engineering culture, and shaping the product roadmap alongside the founders.

What You’ll Do
  • Architect & Build: Design, implement, and scale our core infrastructure, data pipelines, and end-to-end agentic workflows from the ground up.
  • Own the Stack: Take complete ownership of entire product verticals—from robust backend systems and API integrations to custom frontend widgets and interactive developer tools.
  • Ship at High Velocity: Rapidly prototype and deploy production-ready features, balancing speed with clean, extensible architecture.
  • Shape the Culture: Help interview, mentor, and build out the initial engineering team while establishing robust development and deployment best practices.
  • Collaborate Closely: Work directly with the founders to translate raw market feedback and user needs into beautiful, technical realities.

Who You Are
  • The Ultimate Generalist: You are a full-stack product engineer who loves diving into complex infrastructure but equally cares about building a flawless, intuitive user experience.
  • 0-to-1 Builder: You thrive in ambiguity. You don't need a perfectly spec'd ticket to start building—you figure out what needs to exist and execute.
  • Technical Excellence: You have deep experience with modern application stacks (e.g., React, TypeScript, Python/Node, SQL/NoSQL databases) and are highly comfortable building multi-agent systems, complex data pipelines, or robust API frameworks.
  • Product-Minded: You think like a founder. You care deeply about why we are building something and how it impacts the end-user.
  • High-Agility: You have a bias for action and are energized by a fast-paced startup environment.

What We Offer
  • Highly competitive base salary + significant founding equity package.
  • High-end hardware setup of your choice.
  • The opportunity to be an instrumental, early pillar of a venture-backed company with a massive trajectory.

Compensation
The base pay range for this role is $100,000 – $150,000 per year.

Skills Required

  • Deep experience with modern application stacks, including React, TypeScript, Python or Node.js, and SQL or NoSQL databases
  • Experience building multi-agent systems, complex data pipelines, or robust API frameworks
  • Full-stack product engineering experience
  • Ability to architect and build infrastructure and software from the ground up
  • Ability to work effectively in ambiguity and execute without fully specified requirements
  • Product-minded approach focused on user impact and end-user experience
  • Experience mentoring, interviewing, or helping build an engineering team
Am I A Good Fit?
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The Company
5 Employees
Year Founded: 2026

What We Do

Riften is an artificial intelligence infrastructure company building an “earned intelligence” layer for businesses. Its OpenAI- and Anthropic-compatible gateway routes each LLM request to a cost-effective model while preserving existing applications and provider accounts. As customer work generates evaluations and outcomes, Riften uses that evidence to improve routing and train private models on open weights, helping companies reduce inference costs and operate AI on infrastructure they control.

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