Key skills
PythonLarge Language Models (LLMs)Agent frameworksNeo4jCypher query developmentRetrieval systems evaluationSearch systems evaluationAgent-based systems evaluationObservability and tracing tools e.g.Observability and tracing tools LangfuseDockerCloud application deploymentGitLabCI/CD pipelinesNeo4j MCP Cypher ServerText2CypherKnowledge graph schema designGraph data modelingAWS ECS/FargateAIGenAILLMAgenticSnowflakeAWSECSFargateBedrockSaaSCI/CDCommunication
About this role
Quantori is seeking a Lead AI Software Engineer to drive the development of an AI-driven data retrieval and synthesis platform using knowledge graph technologies. The role involves enhancing agent capabilities, translating use cases into queries, and serving as a technical liaison with Neo4j and vendor teams.
Responsibilities:
- Develop and enhance the retrieval of agent capabilities against refreshed KG data
- Understand the updated KG data model and translate business and scientific use cases into Cypher queries
- Refactor the KG agent to leverage vendor-provided MCP tooling and the updated graph schema
- Integrate Neo4j-native query generation and retrieval technologies, including MCP Cypher Server and Text2Cypher frameworks
- Design and execute performance evaluations comparing the refreshed knowledge graph and refactored agent against the current implementation
- Serve as the technical liaison with Neo4j and data vendor support teams
- Document data model changes, retrieval logic, architectural decisions, and evaluation findings
Requirements:
- Strong Python software engineering experience
- Experience building AI applications using LLMs, tool-calling, and agent frameworks
- Working knowledge of Neo4j and Cypher query development
- Experience evaluating and benchmarking retrieval, search, or agent-based systems
- Experience with observability and tracing for agentic systems such as Langfuse or similar
- Familiarity with Docker and containerized application development
- Experience deploying applications in cloud or enterprise environments
- Familiarity with GitLab development practices, including pull requests, code reviews, and CI/CD pipelines
- Strong system design, documentation, and communication skills
- Ability to collaborate effectively with internal stakeholders and external teams
- Neo4j-native GenAI tooling (Neo4j MCP Cypher server, Text2Cypher)
- Knowledge graph schema design and graph data modeling
- Snowflake Cortex and/or AWS Bedrock
- Containerized microservices (Docker)
- Deploying applications to AWS ECS/Fargate
- Biomedical or life sciences data experience
- Evaluating LLM- or agent-based retrieval systems
- Neo4j SaaS / Aura environments and graph performance tuning