Software Engineer, Fullstack

Reposted 16 Days Ago
San Francisco, CA
Hybrid
190K-250K Annually
Mid level
Artificial Intelligence • Information Technology • Software
The Role
Develop the core systems for multimodal AI models, focusing on building model serving platforms and enhancing developer experience with tools and APIs.
Summary Generated by Built In

Sciforium is an AI infrastructure company developing next-generation multimodal AI models and a proprietary, high-efficiency serving platform. Backed by multi-million-dollar funding and direct sponsorship from AMD with hands-on support from AMD engineers the team is scaling rapidly to build the full stack powering frontier AI models and real-time applications.

About the role

This role offers a unique opportunity to work on the core systems that power Sciforium’s multimodal AI models. You’ll help build the model serving platform working across C++, Python, runtime execution, and distributed infrastructure to create a fast, reliable engine for real-time AI applications.

You’ll gain hands-on experience with performance engineering, learn how large AI models are optimized and deployed at scale, and collaborate closely with ML researchers and experienced systems engineers. If you enjoy delighting customers with a great Developer Experience, care deeply about performance, and want exposure to the full AI stack, this role provides both high-impact work and strong growth potential.

What you'll do
  • Interactive AI Chat interface: Design and build a low-latency, chat-like interface for users to test our LLMs.

  • Developer Console: Build the mission-critical UI where users generate API Keys, set budget limits, and view real-time usage graphs

  • Payments & Billing: Integrate Stripe (or similar) to handle complex subscription models.

  • Documentation Portal: creating a dynamic API reference section

  • CLI/SDK Integration: Write simple client-side wrappers to help users connect to our API endpoints easily.

  • Backend APIs: Building secure API gateways and implementing low latency streaming solutions.

Ideal candidate profile
  • Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience)

  • 3+ years of software engineering experience, with a focus on front end development.

  • Strong proficiency in Typescript, Python.

  • Understanding of responsive design, and UX fundamentals

  • Strong collaboration and communication skills, with the ability to work effectively across engineering and ML teams.

  • Comfortable working from the office and contributing to a fast-moving, high-ownership team culture.

Nice-to-have
  • Experience with ML systems engineering, open source inference engine like vLLM, Sglang, or TRT-LLM

  • Streaming Expertise: You understand the difference between WebSockets and Server-Sent Events (SSE) and know how to handle "jittery" network streams without freezing the UI.

  • Billing integration: Experience integrating Stripe Elements, managing webhooks for payment success/failure, and handling "SaaS" logic (pro-rating, tiers).

  • Documentation Mindset: You appreciate good DX (Developer Experience). You know how to render an API spec into a readable web page.

  • Python/Backend Knowledge: You can read a FastAPI or vLLM backend codebase to understand how data is being sent to you

Benefits include
  • Medical, dental, and vision insurance

  • 401k plan

  • Daily lunch, snacks, and beverages

  • Flexible time off

  • Competitive salary and equity

Equal opportunity

Sciforium is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

Top Skills

C++
Fastapi
Python
Stripe
Typescript
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The Company
HQ: San Francisco, CA
7 Employees
Year Founded: 2024

What We Do

Sciforium is pioneering the future of AI infrastructure and research. Backed by AMD and SignalFire, we're developing byte-native multimodal foundation models while delivering serverless LLM serving at a fraction of traditional costs.

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