Job
Description
Your mission As a Software Engineer II AI, you will be at the forefront of building agent-based systems and intelligent pipelines that combine structured geospatial data with unstructured content. You ll collaborate with AI researchers, data scientists, and product engineers to deliver scalable, high-performing solutions. If you thrive on pushing the boundaries of what AI can do in the real world especially in dynamic environments like map making this is the role for you. Your Tasks Design and develop agentic systems using Python and frameworks like Lang Chain or Haystack Build and optimize scalable Retrieval-Augmented Generation (RAG) pipelines using LLMs and vector stores Integrate AI reasoning engines with data sources (SQL, NoSQL, REST APIs, file systems) Enhance system observability and monitoring for intelligent agents and workflows Implement testable, modular, and well-documented code with focus on production-readiness Collaborate with ML and backend engineers to tune performance and cost-efficiency Stay up-to-date with the latest developments in LLMs, multi-agent systems, and semantic retrieval What you should bring along Bachelor s or Master s in Computer Science, Artificial Intelligence, or equivalent 3+ years of experience in software development, with at least 2+ years in AI/ML systems Strong programming skills in Python, including async and multiprocessing capabilities Deep understanding of LLM integration patterns (OpenAI, Hugging Face, etc.) Experience building scalable RAG architectures with vector databases like FAISS, Weaviate, or Pinecone Familiarity with prompt engineering, semantic search, and knowledge graphs Proficiency in designing backend services with RESTful APIs and microservices Working knowledge of containerization (Docker), CI/CD pipelines, and cloud platforms (preferably AWS) Excellent communication and documentation skills Who are you Develop, extend and maintain AI-powered software products in an innovative and iteratively growing environment Implement tools to enhance both automated and semi-automated map data processing, combining backend/service-based software stacks and AI-based agentic workflows Build dashboards or monitoring systems to visualize agent reasoning and RAG system metrics
