Solutions Engineer (India Startup Program)

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.