Senior Software Engineer, Data & AI

Vendelux

About The Position

Vendelux is transforming how companies discover, evaluate, and maximize the impact of events. Event marketers are the driving force behind pipeline and brand — yet events remain one of the least optimized and most opaque marketing channels. Vendelux changes that. 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. Customers often describe Vendelux as an event marketer’s dream. A key part of this is our growing network of event organizer partnerships — where organizers share first-party attendee and sponsorship data, and in return gain access to valuable market insights. In addition, 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. This allows teams to maximize pipeline generation and make every event materially more impactful. Founded in 2021, Vendelux is a Series A SaaS company backed by leading investors including FirstMark, with a recent $14M round. Our team brings experience from companies like Bain, ZoomInfo, Shutterstock, Compass, Forter, Airbnb, and more. We’re looking for a Senior Engineer, Data & AI who thrives at the intersection of software engineering, data engineering, and applied AI to build production-grade systems. You’ll develop, deploy, and scale features that sit at the core of our product. This role is perfect for someone motivated more by impact than method, loves to solve data problems using whatever means necessary, and is eager to see their output shape the user experience.

Requirements

5+ years of professional experience in software engineering or data engineering, with at least 3+ years building AI/ML-driven products.
Strong programming skills in Python and proficiency in SQL.
Experience with modern AI frameworks (eg HuggingFace, LangChain, etc.) and designing data pipelines (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, with the ability to balance research and engineering tradeoffs.
Demonstrated ability to translate business problems into data solutions that drive business value.
Proven track record of shipping user-facing features with measurable impact.
Excellent written and verbal communication skills; ability to collaborate across data, engineering, and product teams.

Nice To Haves

Startup experience preferred.

Responsibilities

Design & Build AI-Powered Features: Architect, implement, and ship data-driven product features, always starting with the customer problem first. From prototyping through production, you’ll apply the right level of technology (whether simple heuristics or advanced AI) to deliver impact.
Build for Production: Build maintainable and scalable systems, including writing clean, testable code, integrating with new and existing data pipelines, and deploying solutions and services into cloud environments.
End to End Solution Delivery: Operate as an end-to-end developer in a fast paced startup. This involves identifying opportunities, prototyping solutions, securing stakeholder support, and productionalizing features that deliver measurable business value.
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.
Collaborate Cross-Functionally: Work with business stakeholders and other engineers to turn customer problems into technical requirements and impactful features.
Promote Best Practices: Establish and evangelize standards for AI/ML engineering and data quality across the team.

Stand Out From the Crowd

Upload your resume and get instant feedback on how well it matches this job.

Upload and Match Resume