Senior Data Engineer, Product Data Systems

BforeAI is an innovative and rapidly expanding scale-up dedicated to deterring cybercrime through cutting-edge predictive and preemptive technologies. We've harnessed the power of prescriptive AI to revolutionize the way we tackle cyber threats, stopping attacks before they launch.

Named by Gartner® in 41 reports over the last 3 years (14 in 2025 alone!) and recognized as a Tech Innovator for Preemptive Cybersecurity in the 2025 Emerging Tech report, BforeAI is the industry’s fastest, most accurate solution for automated protection against online fraud.

Join us in the fight for a safer cyberspace!

🚀 Why it’s great to work here

We are a location-independent company with a fully distributed team. We believe diversity of experience, background, and thinking leads to stronger teams and a better product. We value autonomy, intellectual honesty, practical decision-making, and engineers who take ownership of outcomes rather than waiting for perfectly defined tasks.

We offer an intellectually stimulating company environment and you’ll be working with a bright, dedicated team from across the globe. Additionally, we offer flexible time off, sick days, all public holidays, and stock options.

✨ What’s cool about this job

We are building the data and intelligence foundation required to turn large, diverse sources of threat data into reliable, explainable, and actionable protection for our customers. You will work with a dedicated global team on technically difficult problems involving cybersecurity, distributed systems, data engineering, machine learning, and SaaS product development.

We are hiring a Senior Data Engineer to build the production services and pipelines that acquire, normalize, enrich, relate, score, and deliver threat intelligence through BforeAI’s customer-facing SaaS product.

📣 What you’ll be doing

This is a hands-on product-engineering role. You will design systems and write production software for event-driven data processing and we need an engineer who understands when a managed service is appropriate, when custom code is necessary, and how to deliver either choice as a reliable product capability.

Build product data services

• Design, implement, test, deploy, and operate production services for ingestion, normalization, enrichment, identity resolution, scoring, and intelligence delivery.

• Build maintainable pipeline workers, event consumers, APIs, scheduled processes, and supporting libraries rather than relying exclusively on notebooks, visual workflows, or vendor configuration.

• Own the complete software lifecycle, including architecture, implementation, testing, deployment, monitoring, incident response, and improvement.