LLM Engineer Freelancer

Role Overview

This freelance LLM Engineer role focuses on integrating AI features into existing production systems using Python, Node.js, or Ruby. You'll build RAG pipelines, work with vector databases, and implement LLM-powered features like chat, summarization, and smart search. The position is delivery-oriented, not ML research, and requires strong engineering skills to work directly with clients on practical AI solutions.

Perks & Benefits

Flexible part-time or full-time freelance schedule with B2B contract. Opportunity to work with a network of tech professionals on diverse projects. Remote collaboration with clients, allowing autonomy and direct impact on product features. Career growth through exposure to cutting-edge AI integration and client advisory.

Full Job Description

We're building a network of LLM Engineers who can design, build, and integrate practical AI features into existing products. We're looking for people to collaborate with on a freelance basis - part-time or full-time, depending on project needs.This role is focused on delivery, not ML research. What matters most is your engineering foundation and your ability to integrate AI into real production systems using Python, Node.js, or Ruby codebases.RequirementsWhat we're looking forStrong software engineering background - Python, Node.js, or RubyHands-on experience integrating LLM APIs into production systems (OpenAI, Anthropic, or similar)Ability to design pragmatic AI solutions within existing architecturesExperience building RAG pipelines, embeddings, and vector searchUnderstanding of cost, latency, and reliability constraints of AI systemsAbility to work independently with clients and set realistic expectationsBackground in big data or data pipelines is a big plusEnglish B2/C1Availability part-time or full-time (B2B contract)What You'll DoAdd AI functionality into existing Python, Node.js, and Ruby codebasesBuild LLM-powered features: chat, summaries, classification, smart search, document Q&ADesign lightweight RAG pipelines using embeddings and vector searchWork with vector DBs (pgvector, Pinecone, Qdrant)Implement safe, reliable LLM endpoints (OpenAI, Anthropic, Azure)Work directly with clients to shape AI features and reduce manual effortAdvise clients when NOT to use AI and navigate trade-offs around latency, accuracy, and costWhat do we mean by freelance? Read more at Monterail Tech NetworkPlease mention the word **WINNERS** and tag RMmEwMTo0Zjk6YzAxMzo3ZjU5Ojox when applying to show you read the job post completely (#RMmEwMTo0Zjk6YzAxMzo3ZjU5Ojox). This is a beta feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human.

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