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.

About the Role

AI is no longer an engineering story at Vendelux. Its 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. Were 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. Youll build the MCP servers agent pipelines context frameworks and orchestration layers that make AI genuinely useful across every team - not just for the engineers whove already figured it out on their own. The work is hands-on and technical. The impact is company-wide.

If youre 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 were looking for.

What Youll 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: / 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 persons breakthrough becomes everyones 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 isnt a chatbot. Its a composition: the right MCP integrations the right document access the right memory system the right workflows assembled into something that genuinely serves a functions real work

• Work closely with domain experts to turn institutional knowledge into something an agent can act on; the best agents are co-created not handed down

• Given Vendeluxs focus on event intelligence and pipeline theres particular leverage in agents that understand our data models account scoring and sales workflows

Own the hard infrastructure problems

• Manage the access vs. safety tension: permissions scoping token budgets rate limiting observability dashboards guardrails that enable rather than block

• Maintain reliability across agent infrastructure as the system grows: graceful degradation fallback models cost tracking

• Evaluate frontier models new MCP tooling emerging agent frameworks and integrate whats worth integrating before competitors catch up

What Were Looking For

Technical depth is the baseline. The ability to move others up the proficiency curve is what makes you exceptional in this role.

Required

• Strong software engineering fundamentals. Youre building real infrastructure that teams depend on not configuring existing tools

• Deep hands-on experience with frontier AI agents (Claude Code Codex or equivalent) and the context engineering that makes them actually useful in complex codebases

• Practical production experience building with LLM APIs: tool use multi-turn state system prompt architecture structured outputs multi-agent orchestration

• Hands-on experience with MCP or similar integration frameworks. Youve connected agents to real production systems not just toy examples

• Experience designing for non-technical users: the agent that works for a software engineer is not the same as the one that works for a sales rep or an ops manager

• Comfort working cross-functionally. Youll spend as much time talking to a head of sales or a product lead as you will writing code

Nice to Have

• Background in platform engineering developer tooling or data engineering

• Experience with proactive/scheduled agent systems (not just request-response)

• Familiarity with vector stores RAG pipelines or knowledge graph approaches for agent context

• Experience with CI/CD automation involving AI agents

• Exposure to B2B SaaS data models CRM/MAP integrations or event/attendee data

What Staff Means Here

Staff isnt a senior role with a better title. It means:

• You identify the highest-leverage problems across the company without being told what they are

• You define the technical direction for AI infrastructure and hold the standard across teams

• You operate with wide autonomy and are accountable for outcomes not just execution

• You bring other engineers along: mentoring documenting setting patterns others can follow

Why This Role Why Now

The gap between AI-native teams and everyone else is widening fast. At Vendelux were at an inflection point: our data assets event intelligence attendee behavior account signals are exactly the kind of domain-specific context that makes AI agents genuinely powerful rather than generic.

The AI Enablement Engineers job is to make that advantage real across every team. To make intelligence self-service the same way DevOps made infrastructure self-service. One afternoon of setup connecting the right agent to the right data and deploying it where a team already works creates a permanent productivity gain that compounds.

Were looking for the person who already knows this and wants the scope to do it at scale.

Not all candidates will check all of the requirements listed above and thats ok! We are open to great people from non-traditional backgrounds.

Vendelux is proud to be an equal opportunity workplace. We are committed to equal opportunity regardless of race color ancestry religion gender gender identity parental or pregnancy status national origin sexual orientation age citizenship marital status disability or veteran status.

Required Experience:

Staff IC