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Vendelux is a Series B SaaS platform that brings transparency and AI-driven intelligence to event marketing—a historically unmeasurable channel. The company helps enterprises discover, evaluate, and optimize their event strategy using proprietary insights across hundreds of thousands of events globally, powered by partnerships with event organizers and AI-driven capabilities like their Meetings product, which identifies high-value attendees and books 1:1 meetings.
As a Senior AI Engineer, you will research, build, and ship AI-powered product capabilities that improve user workflows, accelerate insights, and drive measurable business value. You'll establish AI as a foundational layer of the Vendelux product experience, with a focus on agentic systems, LLMs, data, and scalable AI infrastructure.
Key responsibilities include:
- 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.
- Enhance User Experience Through AI: Translate business problems into AI solutions that improve workflows and drive measurable value.
- Build Agentic Chat Across the Product: Own the architecture and integration of agentic chat capabilities throughout the platform—designing systems that allow AI agents to reason, take action, and surface insights across every product surface.
- Establish patterns for how agents interact with internal data, external tools, and user workflows, turning conversational AI into a foundational layer.
- Build for Scale and Reliability: Architect multi-tenant AI infrastructure meeting performance, latency, and cost requirements of a growing B2B SaaS product. Own observability, evaluation frameworks, and guardrails to keep AI features production-grade.
- Partner Across Product and Engineering: Work closely with product, data science, and application engineering teams to translate business requirements into AI systems.
- Serve as a thought partner to leadership on the AI roadmap, influencing product differentiation through AI.
Required qualifications: 4+ years professional software or data engineering experience with 3+ years building AI/ML-driven products. Strong Python and SQL skills. Experience with modern AI frameworks (HuggingFace, LangChain, etc.) and data pipeline tools (Airflow, Dagster). Solid understanding of cloud infrastructure (AWS, GCP, Azure). Production experience with LLMs and generative AI, including prompt engineering, RAG, and deployment. Strong grasp of fundamental data science and ML techniques. Demonstrated ability to translate business problems into data solutions with measurable impact. Proven track record shipping user-facing features. Excellent communication and cross-functional collaboration skills.
