2 months ago
Milpitas, CA, USA or Vancouver, WA, USAStaff+
Base Salary
$220k - $235k/yr
Responsibilities
- Architect and build Saviynt’s AI Security platform for enterprise identity and privileged access.
- Design and develop scalable Go microservices for the Cloud Control Plane and distributed Edge Backends.
- Build cloud control-plane capabilities for policy management, AI governance, discovery orchestration, analytics, reporting, and APIs.
- Develop distributed Edge Backends operating as local Points of Presence across enterprise locations and customer data centers.
- Design resilient Cloud-to-Edge-to-Endpoint policy synchronization with secure fail-closed enforcement during connectivity failures.
- Build discovery services covering cloud resources, on-premises infrastructure, endpoints, applications, databases, and AI agents.
- Develop access-brokering capabilities for privileged access to applications, machines, and services.
- Design highly available, observable, and resilient distributed systems using cloud-native technologies.
- Mentor engineers, lead architecture discussions, and drive engineering best practices.
- Build capabilities to discover, govern, and secure AI agents, automation frameworks, MCP servers, and agentic applications.
- Use AI-assisted development throughout design, implementation, testing, documentation, deployment, and operations.
Requirements
- At least 1 year of Associate Principal-level backend software engineering experience.
- Expert-level Go development experience.
- Deep experience building distributed systems and microservices.
- Experience with Kubernetes, Docker, gRPC, REST APIs, and cloud-native platforms.
- Experience with PostgreSQL, Redis, Kafka, NATS, or similar distributed infrastructure.
- Strong understanding of networking, authentication, authorization, TLS, proxies, and distributed caching.
- Enterprise security, IAM, PAM, Zero Trust, or networking-product experience is highly desirable.
- Hands-on experience with AI-assisted development tools such as GitHub Copilot, Cursor, Claude Code, Windsurf, or ChatGPT.
- Understanding of AI application architectures involving LLMs, RAG, AI agents, orchestration frameworks, and MCP.
- Familiarity with AI SDLC practices including automated testing, secure coding, CI/CD automation, observability, and responsible use of AI-generated code.
- Strong technical leadership, architecture, mentoring, and communication skills.
Benefits
- Growth and learning opportunities through challenging work with direct customer impact.
- Welcoming and positive work environment.
- Annual security training and adherence to company information-security and privacy policies.
- Equal opportunity employment environment.
Tech Stack
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