Staff AI Engineer

Vendelux is transforming how companies discover, evaluate, and maximize the impact of events. We provide the system of record for event marketing, giving teams the data and insights they need to make smarter, more strategic decisions. Our AI-powered platform delivers proprietary insights across 250,000+ events, helping high-growth companies identify where their ideal customers will be, maximize ROI, and turn events into a scalable growth channel.

Vendelux Meetings helps customers turn event insights into action, using AI to identify high-value attendees and automatically book 1:1 meetings with the right prospects at conferences. Founded in 2021, Vendelux is a Series A SaaS company backed by leading investors including FirstMark, with a recent $14M round.

Key Responsibilities:

• Applied AI Innovation: Research and apply modern methods (AI agents, LLMs, RAG, embeddings, supervised/unsupervised learning) to power new product capabilities, prioritizing impact and speed over perfection.
• Enhance User Experience Through AI: Translate business problems into AI solutions that improve user workflows, accelerate insights, and drive measurable value.
• Build Agentic Chat Across the Product: Own the architecture and integration of agentic chat capabilities throughout the Vendelux platform, designing the underlying systems that allow AI agents to reason, take action, and surface insights.
• Build for Scale and Reliability: Architect multi-tenant AI infrastructure that meets the performance, latency, and cost requirements of a growing B2B SaaS product. You'll own observability, evaluation frameworks, and guardrails.
• Partner Across Product and Engineering: Work closely with product, data science, and application engineering teams to translate business requirements into AI systems.

Required Qualifications:

• 4+ years professional experience in software or data engineering
• 3+ years building AI/ML-driven products
• Strong Python programming skills and SQL proficiency
• Experience with modern AI frameworks (HuggingFace, LangChain, etc.)
• Data pipeline design experience (Airflow, Dagster, or equivalent)
• Solid understanding of cloud-based infrastructure (AWS, GCP, or Azure)
• Experience applying LLMs and generative AI in production, including prompt engineering, RAG, and LLM deployment
• Strong grasp of fundamental data science and machine learning techniques
• Proven track record of shipping user-facing features with measurable impact
• Startup experience preferred