AI Backend Engineer

Description

Cyera is reshaping the reality of cloud data security. Backed by the world’s leading cyber investors and led by a solid and dynamic team of technical and industry experts, Cyera is scaling fast and gaining incredible market traction.

Almost every company in the world today is using cloud services (AWS, GCP, Azure), but companies struggle in understanding what data they are storing and where. This is where Cyera comes in!

Cyera scans entire customer environments in minutes and provides immediate insights into what cloud assets exist, the data they hold, and alerts if sensitive data is exposed. Our service lets IT security teams actually locate and remediate data exposure issues, so to eliminate the next big data leak.

We see an overwhelming amount of demand for Cyera's solution and we're growing our engineering department to meet that need. If you’re up to tackle problems of massive scale (literally), come join the team!

As a Senior AI Backend Engineer

You Will Be Working With Tons Of Data! Our Customers Store Petabytes Of Cloud Assets, And We’ll Want You To

• Work with the latest cloud services to fetch the right information
• Research and find innovative ways to process big data into insights
• Always optimize! Be very mindful of resources - costs and runtime
• Develop and scale AI-powered backend systems in production environments – a solid engineering foundation is a must
• Take part in deploying innovative ML models – including LLMs and other advanced AI systems – into real-world, high-scale environments
  
  

• Work with PMs to finalize product requirements and scope
• Collaborate tightly with Data Scientists and Researchers – helping translate experimental models into robust, high-performing features
• Drive and support end-to-end model lifecycle in production – from experimentation to deployment and monitoring
• Think 80/20 - we’re a lean startup and time is crucial. Only develop what brings value
• Apply and integrate classic ML techniques like embeddings, clustering, and dimensionality reduction to power AI features
  
  

• Locate bottlenecks in our pipeline and help fix them
• Automate and orchestrate our processes to make them more efficient
• Always improve our production monitoring and visibility to handle issues quickly