Meedan

Full-stack Engineer

• Lead experimentation on retrieval-augmented generation (RAG) approaches for question answering over a Neo4j knowledge graph.
• Develop and refine evaluation frameworks (test sets, LLM-as-a-judge rubrics, failure mode analyses, etc.).
• Investigate and implement strategies for handling conflicting, incomplete, or time-sensitive information.
• Translate product requirements into ML constraints and possibilities.
• Collaborate with engineers to validate feasibility and de-risk system architecture.
• Focus on experimentation and implementation for our Python-based knowledge service.
• Design, test and implement retrieval strategies, evaluate system trustworthiness, and help define how the service handles conflicting or outdated information.
• Work closely with product and engineering teams to ensure our AI/ML foundations are technically strong, reliable, and aligned with product goals.

Senior Software Engineer, Applied Research

Machine Learning Engineer

• Architect and implement ingestion pipelines that transform raw documents into structured Neo4j knowledge graphs
• Build and refine the Python/FastAPI service exposing ingestion and Q&A endpoints
• Optimize retrieval and answering workflows for performance, cost, and maintainability
• Investigate and implement strategies for handling conflicting, incomplete, or time-sensitive information
• Collaborate with researchers to integrate experimental retrieval/answering strategies into production
• Ensure code quality through testing, documentation, and observability
• Support scaling from pilot-ready prototypes to production-ready services

Senior Software Engineer, Applied Research

Senior Software Engineer, Machine Learning