AI/LLM Engineer

We provide software engineering and data specialists to international clients who want people, not vendors. Our engineers work embedded in client teams on real problems — not slide decks. We invest in your growth: certifications, learning time, architecture access, and honest feedback from people who know what they're talking about.

• Built something with LLMs that actually runs in production
• Solid Python skills — clean code
• Working knowledge of RAG and its challenges
• Experience with at least one agent framework (LangChain, LlamaIndex, LangGraph)
• Familiarity with vector databases (Qdrant, Weaviate, Pinecone, pgvector)
• Knowledge of REST APIs, Docker, cloud basics (AWS / Azure / GCP)
• English B2+ for client-facing communication

Nice to have:

• Experience evaluating LLM outputs (RAGAS, LangSmith, Arize or similar)
• MLflow or another experiment tracking tool
• Databricks, Azure AI Foundry or AWS Bedrock
• Fine-tuning experience (LoRA, PEFT, hands-on)
• Kafka or streaming pipelines for real-time AI use cases

• Building LLM-powered applications and RAG systems for enterprise clients
• Designing and implementing AI agents (LangChain, LangGraph, CrewAI or similar)
• Integrating LLMs (OpenAI, Anthropic, Gemini, open-source) into existing systems
• Building data ingestion pipelines: chunking, embedding, vector indexing
• Writing production-grade Python code — APIs, tests, containers, the full stack
• Working directly with clients: understanding their requirements, presenting solutions
• Doing code reviews, writing docs, contributing to team engineering standards