Join our team as an AI-Native Software Engineer, where you'll be instrumental in building and deploying production-ready software powered by AI. This role emphasizes applying AI-native methodologies throughout the engineering lifecycle, ensuring high standards of quality, compliance, and continuous process improvement. You'll work at the cutting edge, integrating AI deeply into software development to create impactful solutions and enhance operational efficiency.

Design and implement sophisticated multi-agent orchestration pipelines using LangGraph. Construct and maintain hybrid retrieval systems leveraging Neo4j knowledge graphs and Qdrant vector search. Develop robust FastAPI backend services with async I/O and Pydantic v2 models. Build dynamic React 18/TypeScript frontend features, including graph editors and real-time streaming UIs. Integrate enterprise protocols such as A2A, MCP, and AG-UI, and connect to ALM/PLM tools via REST and GraphQL APIs. Implement dual-tier agent memory systems and build DAG-based workflow compilation. Deploy and manage containerized services using Docker, Azure Bicep, and CI/CD pipelines, serving both on-prem and cloud-hosted LLM models.

This role requires a minimum of 4 years in professional software engineering, with at least 2 years focused on LLMs, agent frameworks, or ML systems in production. A strong command of async Python and modern React/TypeScript is essential, alongside experience with graph databases or knowledge graph systems. You should be comfortable taking ownership of features across the full stack, from API to UI and deployment. A 15-year full-time education and a minimum of 3 years of experience in Digital Full Stack Development are mandatory.