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# Full Stack AI Engineer

- **Company:** Job Juncture
- **Location:** San Francisco, CA, United States
- **Experience:** Experienced
- **Salary:** $150,000.0 - $200,000.0
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Databases, Python (Programming Language), Knowledge-Based Systems, PostgreSQL, Machine Learning, Node.Js, Open Source Technology, Performance Tuning, OpenAI, Next.js, Search Technologies, Software Deployment, Software Engineering, Data Streaming, Systems Integration, TypeScript, Speech Recognition, WebSocket, WebRTC, Core Voice Platform, Pinecone, Qdrant, Google Cloud, ReactJS, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Llamaindex, Backend, Agentic-AI, Fastapi, Pgvector, Weaviate, Speech Synthesis, Front End Software Development, Google Gemini, Model Context Protocol, Model Inference, Serverless Computing, Docker, Golang
- **Published:** October 1, 2026
- **Apply:** https://www.jobjuncture.com/all_jobs/47580

## About the Role

The right candidate is comfortable working across frontend, backend, infrastructure, and AI systems. You should enjoy fast-moving startup environments, unclear requirements, rapid iteration, and taking full ownership of what you build., * 4 or more years of professional software engineering experience

 * Proven experience building and launching a product from zero to one
 * Strong experience across both frontend and backend development
 * Experience working at an early-stage startup
 * Strong skills in TypeScript, JavaScript, React, and Next.js
 * Backend experience with Node.js, Python, FastAPI, Go, or similar technologies
 * Experience with PostgreSQL, APIs, cloud infrastructure, and production deployments
 * Hands-on experience integrating large language models into production applications
 * Experience with AI agents, RAG, tool calling, embeddings, or multimodal AI
 * Strong product judgment and the ability to work with limited direction
 * Ability to move quickly while maintaining high engineering standards

Preferred Experience

 * OpenAI, Anthropic, Gemini, or open-source AI models
 * Model Context Protocol and agent orchestration frameworks
 * LangGraph, LlamaIndex, Vercel AI SDK, or similar tools
 * Vector databases such as Pinecone, Qdrant, Weaviate, or pgvector
 * Voice AI, WebSockets, WebRTC, or real-time streaming systems
 * AI evaluations, observability, prompt injection protection, and model security
 * Docker, AWS, Google Cloud, Azure, or serverless infrastructure
 * Experience as an early, founding, or first engineering hire

Ideal Candidate

You are a builder who prefers creating new products over maintaining mature systems. You are comfortable wearing multiple hats, making decisions quickly, and turning incomplete ideas into products that customers can use.

You understand that strong AI products require more than connecting to a model API. You know how to build dependable workflows, evaluate output quality, manage latency and cost, and create safeguards around AI-generated actions.

## Description

Our client is looking for a highly hands-on engineer who can help build and launch AI-native products from the ground up. You will work closely with the founders to turn ideas into production-ready applications and help shape the company's technical foundation., * Build, test, launch, and improve full-stack products from zero to one

 * Develop modern frontend applications using React, Next.js, or similar technologies
 * Build backend services, APIs, databases, and integrations
 * Create AI-powered features using large language models and multimodal models
 * Build AI agents that can use tools, complete workflows, and interact with external systems
 * Develop retrieval-augmented generation, embeddings, vector search, and knowledge systems
 * Integrate voice AI, speech-to-text, text-to-speech, or real-time conversational systems
 * Implement model routing, structured outputs, tool calling, and human approval workflows
 * Build evaluation, monitoring, and testing systems for AI performance
 * Improve application speed, reliability, scalability, security, and AI inference costs
 * Work directly with founders, users, and product stakeholders
 * Help make product, architecture, and technology decisions


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