📅 Jul 18, 2025
Bring up and optimize open-source and customer-provided AI models on Cerebras CSX systems, working across model translation, compiler optimization, runtime integration, debugging, and performance tuning.
LLM Engineer - Freelancer
📅 Jul 28
PythonNode.jsRubyLLM API Integration
📜 Description
- Deliver AI functionality in existing Python, Node.js, and Ruby codebases
- Design lightweight RAG pipelines using embeddings and vector search
- Use vector databases including pgvector, Pinecone, and Qdrant
- Implement reliable LLM endpoints with OpenAI, Anthropic, or Azure
- Work directly with clients to shape AI features, reduce manual effort, and advise on trade-offs
🛠️ Requirements
- Strong software engineering background - Python, Node.js, or Ruby
- Hands-on experience integrating LLM APIs into production systems (OpenAI, Anthropic, or similar)
- Ability to design pragmatic AI solutions within existing architectures
- Experience building RAG pipelines, embeddings, and vector search
- Understanding of cost, latency, and reliability constraints of AI systems
- Ability to operate independently with clients, take ownership of delivery, and set realistic expectations
- English B2/C1
- Availability of 15-40 hours per week (B2B contract)
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.
Requirements
What we’re looking for
- Strong software engineering background - Python, Node.js, or Ruby
- Hands-on experience integrating LLM APIs into production systems (OpenAI, Anthropic, or similar)
- Ability to design pragmatic AI solutions within existing architectures
- Experience building RAG pipelines, embeddings, and vector search
- Understanding of cost, latency, and reliability constraints of AI systems
- Ability to operate independently with clients, take ownership of delivery, and set realistic expectations
- Background in big data or data pipelines is a big plus
- English B2/C1
- Availability of 15-40 hours per week (B2B contract)
What you'll do
- Deliver AI functionality within existing Python, Node.js, and Ruby codebases
- Build LLM-powered features: chat, summaries, classification, smart search, document Q&A
- Design lightweight RAG pipelines using embeddings and vector search
- Leverage vector DBs (pgvector, Pinecone, Qdrant)
- Implement safe, reliable LLM endpoints (OpenAI, Anthropic, Azure)
- Collaborate directly with clients to shape AI features and reduce manual effort
- Advise clients when NOT to use AI and navigate trade-offs around latency, accuracy, and cost
What do we mean by freelance?
- Read more at Monterail Tech Network
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