Software Engineer, Fullstack

Sciforium•San Francisco, CA

2d•Onsite

About The Position

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.

Requirements

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 Haves

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

Responsibilities

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.