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AI Application Engineer

Company:
QUICK USA, Inc.
Location:
Torrance, CA, 90504
Posted:
May 02, 2025
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Description:

Summary

A growing startup IT company is seeking a highly skilled AI Application Engineer to join their team. The ideal candidate will play a key role in designing, developing, and deploying API services powered by Large Language Models (LLMs) while integrating seamlessly with existing TypeScript-based backend systems.

Essential Duties

Design, develop, and deploy a Python-based API server with LLM

Build API endpoints using FastAPI

Implement LLM workflows using LangChain/LangGraph libraries

Develop vector search functionality with Qdrant DB

Implement real-time communication with the frontend using WebSockets

Effectively integrate with the existing TypeScript backend

Optimize LLM functionality for performance and cost

Collaborate with team members to improve the overall system

Working Hours, Working style

Monday - Friday; 8 hours a day

Core hours: 9:30 AM – 2:30 PM (Flexible schedule outside core hours)

Working Location

Irvine, CA

Salary/Benefit

$100K - 140K DOE

Health insurance

Retirement plan (simple IRA)

Paid time off (PTO) & sick leave

Holidays

Saturdays, Sundays, and major US holidays

Qualifications

Business-level proficiency in English (spoken and written)

5+ years of professional experience in Python development

Proven experience building and deploying production-level applications using LLMs (e.g., GPT, Claude, Azure OpenAI, or Google Gemini)

Solid understanding of RESTful API design and development

Experience integrating AI features into real-world applications

Experience or interest in the following technologies: FastAPI, LangChain / LangGraphQdrant, or other vector databases. WebSocket communication, Basic knowledge of TypeScript and React for integration with frontend systems

Familiarity with prompt engineering, fine-tuning, or retrieval-augmented generation (RAG)Hands-on experience with OpenAI, Anthropic, or other model APIs in scalable environments

Awareness of AI safety, latency management, and cost optimization strategies

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