Posted May 7, 2026
ASSOCIATE PRINCIPAL SOFTWARE ENGINEER
Saviynt is an identity platform built to power and protect the world at work. With the rise of AI and Agents, the identity perimeter needs to be secured at scale. Come join as founding members of Saviynt’s AI Security team and enable us to build out AI security for the world's leading enterprises. 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 bestwork. WHAT YOU WILL BE DOING
WHAT YOU BRING
7+ years of software engineering experience
Expert-level ability utilizing technologies such as Java, Spring Framework, REST and Microservices
Familiar with AI tools and curious about MCP, A2A, Agentic frameworks. Have a continuous learning mindset and not hesitate to venture into unchartered territory. - Ability to perform research and go deep into platforms is a strong plus. - 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 unit, functional and system integration testing
Extensive understanding of working in an agile environment utilizing Scrum and Kanban
Experience with Git (GitHub/GitLab), automatic deployments, continuous integration
Hands on experience using IntelliJ or Eclipse/My Eclipse IDE, writing Junit test cases, working with Maven/Ant
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
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