Remote Full-Stack Engineer | AI Systems & LLMs | Equity

USA Tech Recruit; San Francisco (CA); On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Equity

Remote-friendly

Job summary

USA Tech Recruit is seeking a Full Stack Engineer AI Systems for San Francisco with remote option. The role focuses on building end-to-end features spanning frontend, backend, and AI integrations, including designing workflows for multi-step tasks and robust AI behavior.

Ideal candidates will have strong full stack experience, API architecture skills, and hands-on work with LLMs, RAG, or AI-powered apps, in a fast-moving startup environment. Equity is offered.

Qualifications

• Strong full stack experience across frontend and backend.
• Experience designing systems with LLMs or AI-powered apps.
• Ability to work in fast-moving environments with evolving requirements.

Responsibilities

• Build end-to-end product features across frontend, backend, and AI integrations.
• Design agent workflows that handle planning, tool use, failure, and recovery across multiple steps.
• Integrate LLMs, memory, and external tools into systems that behave reliably under real-world conditions.
• Design real-time AI interactions with streaming, partial results, and tight latency constraints.
• Improve system reliability, observability, and fallback mechanisms.
• Collaborate closely with ML, backend, and product teams to ship features end-to-end.
• Continuously iterate based on real usage and failure modes.

Skills

Full stack

API design

LLM experience

Ambiguity handling

Ownership

Agile fast-moving environment

Tools

Next.js

Python

Node.js

PyTorch

OpenAI

Anthropic

SQL

NoSQL

Kubernetes

Docker

Job description

USA Tech Recruit is seeking a Full Stack Engineer AI Systems for San Francisco with remote option. The role focuses on building end-to-end features spanning frontend, backend, and AI integrations, including designing workflows for multi-step tasks and robust AI behavior.

Ideal candidates will have strong full stack experience, API architecture skills, and hands-on work with LLMs, RAG, or AI-powered apps, in a fast-moving startup environment. Equity is offered.