Solutions Engineer (India Startup Program)

About Neo4j: Neo4j is the graph intelligence platform that transforms data into knowledge to power the next generation of intelligent applications and AI systems. It includes enterprise-ready knowledge graphs for accurate, explainable, and governed AI; the most comprehensive, trusted, and easy-to-deploy graph capabilities across any environment and data source; and an unmatched ecosystem trusted by 84 of the Fortune 100 and supported by the world’s largest graph community. Intelligence that works. Results that matter. Built to work everywhere and integrate with everything across every cloud for dynamic, personalized, and autonomous AI systems. We deliver quicker results, contextual knowledge, and solutions that impact customers and employees across the business. Our Vision: At Neo4j, we have always strived to help the world make sense of data. As business, society and knowledge become increasingly connected, our technology promotes innovation by helping organizations to find and understand data relationships. We created, drive and lead the graph database category, and we’re disrupting how organizations leverage their data to innovate and stay competitive. Role Summary Help AI-focused startups in Neo4j’s Startup Program succeed with graph + LLM solutions so they adopt Neo4j deeply and grow into long-term, high-value customers. This is a highly technical, customer-facing role focused on helping AI startups onboard successfully, design effective solutions, and scale their Neo4j use over time. The role blends solution architecture, technical advisory, and ongoing customer engagement to support startups from early experimentation through production adoption. Key Responsibilities Technical Leadership for Startup Customers Serve as the primary technical point of contact for a portfolio of AI startups in the program. Guide teams in designing, building, and deploying Neo4j-based architectures. Advise on best practices for Neo4j usage across Aura and self-managed environments, including scaling, performance, and production readiness. Troubleshoot implementation challenges and help customers make sound technical tradeoffs. Graph + AI / LLM Solution Design Help startups design and implement LLM-enabled solutions using Neo4j, including RAG, knowledge graphs, and agent-based architectures. Translate customer AI requirements into concrete Neo4j-centered architectures, patterns, and implementation guidance. Work with common AI frameworks and tooling such as LangChain, LlamaIndex, PydanticAI or ADK, agent frameworks, vector search, and open-source and commercial LLMs. Identify and promote repeatable graph + AI solution patterns across the startup portfolio. Customer Success and Technical Relationship Ownership Own the ongoing technical relationship with assigned startups. Run regular check-ins, track progress, and proactively identify risks or blockers. Help customers move from early experimentation to successful production adoption. Cross-Functional Collaboration Partner closely with the Field AI team to align on architectures, patterns, and technical strategy. Feed real-world startup requirements, usage patterns, and product gaps back to Product and Field teams. Bridge product gaps where needed through third-party tools, integrations, and pragmatic solution design. Enablement and Knowledge Sharing Contribute to internal enablement content, examples, office hours, and best practices for graph + AI patterns. Share lessons learned from startup engagements with broader Field teams. Help standardize playbooks, templates, and reference implementations for the Startup Program. Required Experience and Skills Neo4j and Graph Technology Strong hands-on experience with Neo4j or other graph database, including data modeling, Cypher, clustering/topology, and performance tuning. Demonstrated ability to debug and optimize real-world implementations, including queries, data ingestion, and infrastructure decisions. Solution Engineering and Architecture Backg