PRINCIPAL SOFTWARE ENGINEER, REQUESTS TEAM
Saviynt is an identity authority platform built to power and protect the world at work. In a world of digital transformation, where organizations are faced with increasing cyber risk but cannot afford defensive measures to slow down progress, Saviynt’s Enterprise Identity Cloud gives customers unparalleled visibility, control and intelligence to better defend against threats while empowering users with right-time, right-level access to the digital technologies and tools they need to do their best work.
WHAT YOU WILL BE DOING
Design and develop secure, scalable, multi-tenant software solutions that run seamlessly across major cloud platforms like AWS and Azure
Lead the design and implementation of highly complex, secure, and scalable multi-tenant architectures across cloud platforms
Act as a technical expert and thought leader, influencing product direction and engineering best practices
Drive continuous improvement in engineering processes, tooling, and operational reliability
Collaborate with internal teams to produce software design and architecture
Develop state-of-the-art enterprise identity cloud solutions
Test and deploy applications and systems
Revise, update, refactor and debug code
Ability to start a program from scratch as well as maintain existing services
Develop documentation throughout the software development life cycle
Serve as an expert on applications and provide technical support
WHAT YOU BRING
10+ years of software engineering experience
Expert-level ability utilizing technologies such as Java, Spring Framework,
REST and Microservices
Strong Experience as a Java Engineer developing applications based on
Security principles, cloud platforms (AWS, Azure, or Google Cloud) and
Containerization (Docker, Kubernetes)
Deep understanding of data structures, algorithms, and design patterns
Hands on experience with SQL, ElasticSearch, Redis, CI/CD, AWS Glue, Kafka
Experience in increasing levels of responsibility managing application
development, solution architecture, design and delivery, and process
improvement
Experience with Git (GitHub/GitLab), automatic deployments, continuous
integration
Experience with AI development tools in SDLC such as Amazon Q, Github Copilot, Cursor, and similar productivity assistants
Familiarity with various architectural patterns (e.g., event-driven, microservices, serverless) and their trade-offs