The ideal candidate is a self-motivated, multi-tasker, and demonstrated team-player. We are looking for software engineers who will lead/participate in designing, prototyping, and development of new software products for data privacy. The successful candidate will have experience building distributed systems at cloud scale and delivering customer delight.
You will be collaborating daily with a brilliant team of engineers who are passionate about building high-quality enterprise solutions that will delight the customers.
Responsible for designing and developing application platforms that leverages the Skyflow security and privacy platform
Responsible for designing and developing backend infrastructure to support large scale data and privacy workflows.
Contribute to performance engineering efforts and ensure low latency and high throughput transactions at scale.
Participate in building and implementing effective test strategies and develop software with high agility and zero downtime.
Collaborate with security and privacy engineers to deliver state-of-the-art privacy solutions.
Contribute to building a world-class software team
Experience designing and building high throughput low latency systems.
Deep understanding of algorithms, data structures, scalability, and distributed systems.
Experience with databases, cloud infrastructure, event and data pipelines, and open-source cloud-native technologies.
Experience with continuous integration, designing testable code, and test-driven development.
Proficient in one or more programming languages like Go(preferred), Java, C#, C++, Python.
Proven track record of delivering cloud-native distributed platforms at scale and with a meaningful adoption.
Success at Skyflow demands demonstrable cultural traits such as being a fast learner, adaptable to changing landscape and most importantly a strong believer in being hands-on.
Nice to haves
Some understanding of modern privacy expectations and compliance will be a plus.
Experience building security and privacy applications or infrastructure.
Exposure to machine learning techniques and practices.
BS or MS in Computer Science or related field.
Relevant industry experience or advanced research experience