Staff AI Enablement Engineer

Vendelux is building the category-defining platform for event marketing intelligence.

Events are one of the largest and most impactful marketing channels, yet historically one of the least measurable. Vendelux brings transparency and performance to this space — helping companies discover, evaluate, and optimize their event strategy with data.

Our platform powers thousands of event decisions by delivering proprietary, AI-driven insights across hundreds of thousands of events globally. At the core of our platform is a robust ecosystem of event organizer partnerships — where organizers share first-party data, enabling richer insights for customers while receiving benchmarking and audience intelligence in return. From identifying the highest ROI conferences to enabling targeted meeting programs, Vendelux helps companies turn events into a predictable and scalable growth engine.

In addition, Vendelux Meetings extends our platform by turning insights into pipeline — using AI to identify high-value attendees and proactively book 1:1 meetings between our customers and their ideal prospects at events. This enables go-to-market teams to drive measurable ROI and maximize every event interaction.

Founded in 2021, Vendelux is a Series B SaaS company backed by top-tier investors including FirstMark. We partner with many of the fastest-growing companies in the world, and our team includes leaders from Bain, ZoomInfo, Shutterstock, FanDuel, Compass, Airbnb, Forter and beyond.

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About The Role AI is no longer an engineering story at Vendelux. It’s a company story. The way our sales team prospects, the way product researches, the way ops runs processes, the way data answers questions. All of it is changing fast. We’re looking for a Staff AI Enablement Engineer to be the technical force behind that change.

This role sits at the intersection of deep AI infrastructure and cross-functional impact. You’ll build the MCP servers, agent pipelines, context frameworks, and orchestration layers that make AI genuinely useful across every team - not just for the engineers who’ve already figured it out on their own. The work is hands-on and technical. The impact is company-wide.

If you’re the person at your current company who got everyone on Claude Code, wired up MCP servers for internal tools, and is already running agents 24/7, you might be exactly who we’re looking for.

What You’ll Do Build the shared AI infrastructure layer

• Design, build, and maintain MCP servers that connect our internal systems like Github, Snowflake, Linear, Notion, Slack, and others, to agents running across every function
• Establish and own our context engineering standards: CLAUDE.md / AGENTS.md conventions, shared context/ directories, architecture docs that make our agents deeply aware of how Vendelux works
• Build the memory and persistence layer for long-running agents: session continuity, proactive scheduling, cross-session context
• Own orchestration infrastructure for multi-agent workflows: coordination, sub-agent spawning, token budgets, permission boundaries
• Maintain codebase health as the system scales: shared component libraries, automated quality gates, fragmentation checks, doc validation in the PR pipeline

Drive adoption across every function

• Partner with sales, ops, product, marketing, legal, and data teams to identify where AI can fundamentally change how a team works and build the agents that make it happen
• Get every team to their “aha” moment fast: preconfigured environments, pre-connected tools, skills they can run immediately without debugging
• Build and grow a skills marketplace where anyone can package a workflow and share it company-wide so one person’s breakthrough becomes everyone’s superpower
• Create visibility and healthy competition around AI usage: leaderboards, showcases, Slack channels, all-hands demos that make building contagious
• Identify force multipliers on every team (the people who get it early) and give them the platform and resources to bring their teams along

Build purpose-built agents for non-engineering teams

• Each agent isn’t a chatbot. It’s a composition: the right MCP integrations, the right document access, the right memory system, the right workflows assembled into something that genuinely serves a function’s real work
• Work closely with domain experts to turn institutional knowledge into something …