Neo4j Jobs

Haven Safety AI is building an enterprise learning intelligence layer for safety, designed to help high-risk organizations learn faster from incidents and prevent future occurrences. The platform integrates with existing EHS systems to enhance incident investigation, assessment, and learning processes. It leverages current incident evidence, company knowledge, historical cases, and an industry knowledge graph, with specialized AI agents analyzing various data points to produce traceable assessments. This role is a build-and-operate position focused on the AI and LLM engineering layer, connecting the evidence base and knowledge graph to the product experiences used by investigators and safety leaders. The work is technically demanding and operationally critical, serving enterprise customers in regulated, safety-critical industries where precision, traceability, evaluation, and human oversight are paramount.

Burnt is building the Operating Brain for the global supply chain, a system designed to run businesses on autopilot. We transform historical data from ERP systems into actionable forecasts, ontologies for AI agents, and models tuned on proprietary data. Our initial focus is the food industry, a complex and operationally challenging sector. We are a highly competitive team dedicated to building the future of supply chain operations. This role is for our first dedicated ML hire, responsible for building and evolving the model layer of our system. Models must be production-ready, continuously improving, and cost-effective.

$150k - $275k

CoreStory unlocks the hidden intelligence in legacy code by using AI to surface business logic and technical insights, enabling enterprises to modernize faster and reduce risk. We are seeking an AI Engineer passionate about building intelligent systems that integrate large language models, retrieval architectures, and conversational agents into scalable products. This role is central to the AI engine powering the CoreStory Platform, focusing on developing and optimizing LLM integration, vector search systems, prompt orchestration, agentic systems, and retrieval-augmented generation (RAG) pipelines. You will collaborate with product, data, and infrastructure teams to prototype, productionize, and evolve our AI stack, ensuring accuracy, explainability, efficiency, and cutting-edge capabilities.