Job Overview

As Product Marketing Manager, AI Capabilities & Developer Enablement, you own how Neo4j’s AI capabilities show up to the developer audience, how our technology integrations are positioned, and the sales enablement infrastructure that turns capability stories into field behavior. You translate GraphRAG, agents, agent memory, MCP, and our integration ecosystem into messaging that earns developer trust, then build the plays, decks, and certification that help the field win deals with it.

This is a builder’s role on a small, senior, systems-first team. You own the messaging architecture, the proof, and the field-facing assets for the developer persona, and you pull on teammates, agentic pipelines, and partners to deliver.

The ideal candidate is part developer marketer, part field operator, and part builder. You are comfortable getting hands-on with the product (a free AuraDB instance, a GraphRAG demo, an integration with an agent framework), and equally comfortable turning what you learn into a one-page sales play that a seller can run the next morning.

Key Responsibilities

• AI capabilities messaging for developers: Contributed to the messaging architecture and proof points for Neo4j’s AI capabilities, targeting technical, developer, and AI-engineering audiences. Translate GraphRAG, agents, agent memory, and Cypher AI into credible, differentiated stories that respect developer intelligence.
• Technology integrations: Own positioning and messaging for Neo4j’s integration ecosystem, including agent frameworks (LangChain, LlamaIndex), MCP servers, cloud and data-platform partners (Databricks, Snowflake, Microsoft), and the connectors and APIs developers build with. Make the ecosystem story part of the core narrative, not an appendix.
• Sales enablement infrastructure: Build and maintain the enablement that turns capability stories into field behavior: first-call decks, talk tracks, objection-handling guides, discovery question banks, demo guidance, and live training. Design it as a system the field actually uses, not a pile of one-off decks.
• Win-loss analysis: Partner with sales, sales engineering, and revenue operations to run structured win-loss programs. Surface patterns by competitor, segment, and use case, and feed insights back into messaging and product priorities.
• Sales enablement: Build and deliver enablement that arms global sellers and SEs to handle competitive deals with confidence. This includes objection-handling guides, talk tracks, discovery question banks, demo guidance, and live training sessions.
• Launch support: Partner on AI capability and integration launches, owning developer-facing messaging, demos, and enablement so each release lands with the field and the community.
• Customer zero: Use the product the way our developers do. Prototype with it, build demos, and bring that hands-on credibility into every story you tell.

Requirements/qualifications

• Bachelor’s degree in Marketing, Business, Engineering, or a related field; MBA a plus. 3+ years in product marketing, developer marketing, sales enablement, or go-to-market strategy within the technology/software industry.
• Direct experience marketing to a developer or technical-practitioner audience, ideally for data infrastructure, databases, developer tools, or AI/ML platforms.
• Proven track record building sales enablement that the field actually uses: first-call decks, plays, objection handling, and certification, plus experience running or contributing to a structured win/loss program.
• Technical acumen to get hands-on with the product, read documentation and architecture diagrams, and form a defensible point of view. You do not need to be an engineer today, but you should be able to learn complex technical categories quickly.
• Strong writing and presentation skills. You can write a one-page play and design a 30-minute certification session with equal ease.
• Proven ability to work across product, sales, sales engineering, DevRel, and partner marketing, and to move work forward through influence rather than authority.
• Familiarity with GraphRAG, agents, vector databases, knowledge graphs, or GenAI architectures is a strong plus. Comfort using AI tools in your own workflow is expected; we are an agent-native team.