Freelance LLM Engineer: Production AI & RAG Pipelines

Monterail; Kraków; On-site; PLN 165,312 - 303,072; Part time

Job summary

Monterail is building a network of LLM Engineers to design, build, and integrate AI features into existing products. This role is freelance, part-time or full-time, depending on project needs, focused on delivery rather than ML research.

You'll collaborate with clients, integrate AI into production systems using Python, Node.js, or Ruby, and build features like chat, summarization, classification, smart search, and document Q&A.

Qualifications

• 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 work independently with clients and set realistic expectations
• Background in big data or data pipelines is a big plus
• English B2/C1
• Availability part-time or full-time (B2B contract)

Responsibilities

• Add AI functionality into 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
• Work 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 effort
• Advise clients when NOT to use AI and navigate trade-offs around latency, accuracy, and cost

Job description

Monterail is building a network of LLM Engineers to design, build, and integrate AI features into existing products. This role is freelance, part-time or full-time, depending on project needs, focused on delivery rather than ML research.

You'll collaborate with clients, integrate AI into production systems using Python, Node.js, or Ruby, and build features like chat, summarization, classification, smart search, and document Q&A.