8 hours ago
Responsibilities
- Advise technical leaders, stakeholders, and strategic partners on Graph+GenAI solution architecture and implementation.
- Design, advocate for, and deploy scalable graph database and LLM-based enterprise solutions.
- Discover customer requirements, assess data ecosystems, and translate strategic objectives into production-ready AI applications.
- Lead stakeholder engagement, project scope and priority alignment, risk mitigation, and delivery coordination.
- Develop, test, optimize, and deploy AI applications integrating graph databases, LLMs, and orchestration frameworks.
- Evaluate and improve the performance, scalability, and efficiency of deployed AI applications.
- Create thought leadership, methodologies, documentation, workshops, and training for internal teams and customers.
- Provide field insights to Product and Marketing teams and stay current with generative AI trends and technologies.
Requirements
- At least 5 years of experience architecting and delivering enterprise-grade applications across the software development lifecycle.
- Experience with LLMs, prompt engineering, fine-tuning, LLM providers, and integrating LLMs into applications.
- Advanced proficiency in at least one of Java, JavaScript, Python, or C# with experience delivering maintainable, scalable production code.
- Hands-on experience with Linux, Docker, Kubernetes, and enterprise version control systems such as Git or SVN.
- Expertise deploying and scaling applications across AWS, Azure, or GCP and understanding cloud-native architecture and DevOps practices.
- Knowledge of generative AI frameworks and platforms including LangChain, LlamaIndex, Haystack, AWS Bedrock, Google Vertex AI, and Azure ML.
- Background in data engineering, analytics, or data science, including data pipelines, structured and unstructured data, Hadoop, Spark, Hive, SQL, and NoSQL systems.
- Deep expertise in graph data modeling, Cypher, and graph databases or triple stores such as Neo4j, Amazon Neptune, TigerGraph, Ontotext, or Stardog.
- Strong communication, stakeholder engagement, analytical problem-solving, and team mentoring abilities.
- Willingness and ability to travel up to 50% for customer engagements and strategic discussions.
Benefits
- U.S. employees are eligible for stock option grants, and certain roles are eligible for an annual bonus.
- Benefits include medical, dental, and vision coverage, 401(k), paid time off, and certain leaves of absence.
- The role is based in the United States and requires travel of up to 50%.
Tech Stack
Apache HadoopApache HiveApache SparkAWSAzureC#DockerGitGoogle Cloud PlatformJavaJavaScriptKubernetesLinuxNeo4jPythonSQLSubversion
Categories
Solutions Engineering
About Neo4j
Neo4j builds a native graph database and graph analytics platform for developers and data teams, available as self-managed software and the Aura managed cloud. It powers knowledge graphs, recommendations, fraud detection, and other relationship-centric applications via the Cypher query language and integrations across data tools. Founded in 2007 and headquartered in San Mateo, the privately held company commercializes the open-source Neo4j project with enterprise subscriptions and support.