3 months ago
Responsibilities
- Design and develop Privacy APIs and backend infrastructure for large-scale data and privacy workflows.
- Own integrations with third-party and internal data platforms, data warehouses, REST/GraphQL services, and message queues.
- Design and implement robust, scalable distributed systems with high-throughput and low-latency transactions.
- Ensure system reliability, performance, maintainability, software quality, security, testing, and documentation.
- Build effective test strategies and develop software supporting high agility and zero downtime.
- Collaborate with engineering, product, and infrastructure teams.
Requirements
- Proficiency in one or more programming languages, preferably Go, or Java, C, C++, or Python.
- Experience with GCP, AWS, or Azure cloud platforms.
- Experience developing high-throughput, low-latency systems through performance engineering.
- Familiarity with BigQuery, Snowflake, Kafka, or similar data systems.
- Deep understanding of algorithms, data structures, scalability, and distributed systems.
- Solid understanding of RESTful design, event-driven systems, and security best practices.
- Experience with continuous integration, testable code, and test-driven development.
- Hands-on approach, adaptability, and ability to learn quickly.
Benefits
- Work-from-home expense benefit in the U.S., Canada, and Australia.
- Health, dental, and vision insurance options, varying by country.
- Vanguard 401(k).
- Generous paid time off, flexible hours, and equity.
Tech Stack
Categories
About Skyflow
Skyflow builds a data privacy and runtime AI data control platform for enterprises, securing sensitive data across applications, data stores, and AI models/agents. Its SaaS APIs provide capabilities like vaulting, tokenization, data governance, and data residency to enable safe AI deployment and compliance. Founded in 2019 and headquartered in Palo Alto, it serves Fortune 500s and SaaS providers in financial services, healthcare, retail, travel, and hospitality.