About The Role

Join Vendelux, a company at the forefront of AI integration across all functions. As a Staff AI Enablement Engineer, you will be the technical force behind the company's AI transformation. Your role will involve designing and building the infrastructure that connects internal systems to AI agents, establishing context engineering standards, and partnering with various teams to identify and implement AI solutions. You will have a significant impact on the company's operations and growth.

Design, build, and maintain MCP servers that connect internal systems to agents running across every function.
Establish and own context engineering standards, including conventions, shared context directories, and architecture documentation.
Partner with cross-functional teams to identify where AI can fundamentally change how a team works and build the agents that make it happen.
Technical depth is the baseline. The ability to move others up the proficiency curve is what makes you exceptional in this role
Practical, production experience building with LLM APIs: tool use, multi-turn state, system prompt architecture, structured outputs, multi-agent orchestration
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
Strong software engineering fundamentals. You're building real infrastructure that teams depend on, not configuring existing tools
Hands-on experience with MCP or similar integration frameworks. You've connected agents to real production systems, not just toy examples
Comfort working cross-functionally. You'll spend as much time talking to a head of sales or a product lead as you will writing code
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
Not all candidates will check all of the requirements listed above and that’s ok! We are open to great people from non-traditional backgrounds
Exposure to B2B SaaS data models, CRM/MAP integrations, or event/attendee data
Experience with CI/CD automation involving AI agents
Experience with proactive/scheduled agent systems (not just request-response)
Familiarity with vector stores, RAG pipelines, or knowledge graph approaches for agent context
Background in platform engineering, developer tooling, or data engineering

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