New offer - be the first one to apply!

June 17, 2026

Senior Python AI Engineer (green building)

Senior • Remote

140 - 160 PLN

Warsaw, Poland

About the project

Project for a client that promotes green building design.

Our expectations

  • Python Expert: 5+ years of commercial experience writing production-quality code. Proficiency in building scalable services and APIs (FastAPI, Flask, Django) and comprehensive test suites (pytest).
  • Clean Code & Architecture: Strong advocacy for clean code principles and building modular, maintainable software architectures.
  • Hands-on experience with LangChain or advanced patterns using LangGraph, LangSmith, or LlamaIndex.
  • Agentic Workflows: Proven ability to build autonomous AI agents with tool-calling, function-calling, and complex multi-step reasoning.
  • RAG & Vector Search: Practical expertise in implementing Retrieval-Augmented Generation (RAG) using vector databases (Pinecone, Weaviate, Milvus, Pgvector) and optimizing embedding models.
  • Prompt Engineering: Expert-level skill in prompt design and structured outputs (JSON, Pydantic, Instructor).
  • The "Evals" Mindset: Experience building evaluation frameworks to measure relevance, consistency, latency, cost, and user trust.
  • End-to-End Delivery: Track record of taking AI-powered applications from ideation and prototyping to full-scale production deployment.
  • Data Literacy: Solid understanding of data quality, freshness, and structure impact on model behavior, including building data pipelines for AI consumption.
  • Experience with major cloud platforms (Azure, AWS, or GCP) and their managed AI/ML services (e.g., Azure OpenAI, AWS Bedrock).
  • Experience integrating LLMs into existing product ecosystems via microservices or workflow engines.
  • High proficiency in written and spoken English (min. B2+ level).

Welcome Skills

  • "Getting Things Done" Attitude: Proactive, problem-solving mindset suited for a fast-paced, client-facing environment.
  • Product-First Engineering Mindset: Ownership of the AI lifecycle from ideation and architectural design to production deployment, partnering with stakeholders and iterating based on performance data and user feedback.
  • Stakeholder Communication: Ability to translate complex technical AI concepts into clear business solutions for non-technical stakeholders.