We help EU and US product teams add practical AI features to their existing web products, internal tools, and business workflows.
We are looking for an engineer who can integrate LLMs into products.
What you will work on: * Build AI features for existing web apps and business systems: assistants, copilots, semantic search, document processing, data extraction, and internal automation tools * Design RAG pipelines over client data: chunking, embeddings, vector search, retrieval quality, and source-aware responses * Work with function calling, tool use, structured outputs, streaming responses, and API integrations * Connect AI features with existing REST APIs, databases, CRMs, Google Workspace, email, forms, and internal tools * Communicate with clients or project managers to clarify requirements and explain technical trade-offs
Nice to have: * 3+ years of commercial software engineering experience, preferably backend or full-stack * Hands-on experience shipping LLM / GenAI features to production or near- production environments * Understanding of RAG: embeddings, chunking, retrieval, vector search, prompt context, and retrieval quality * Experience integrating into existing codebases, REST APIs, databases, and third- party systems * Ability to build reliable solutions with error handling, logging, validation, and fallbacks
English B2: able to join client standups, discuss requirements
Format: dedicated team or project-based cooperation
