Associate Principal Software Engineer, Cloud & Edge Backend
Come join us as founding members of Saviynt’s AI Security team and help us build out AI security for the world's leading enterprises.
WHAT YOU WILL BE DOING
-
Architect and build the next-generation AI Security platform for enterprise identity and privileged access.
-
Design and develop highly scalable microservices in Go (Golang) that power the Cloud Control Plane and distributed Edge Backends.
-
Build the Cloud Control Plane responsible for policy management, AI governance, discovery orchestration, analytics, reporting, and APIs.
-
Build distributed Edge Backends that operate as local Points of Presence (PoPs) for headquarters, regional hubs, branch offices, and customer data centers.
-
Design resilient policy synchronization from Cloud → Edge → Endpoint with secure fail-closed enforcement during connectivity failures.
-
Build enterprise-scale discovery services for cloud resources, on-prem infrastructure, endpoints, applications, databases, and AI agents.
-
Develop access-brokering capabilities that enable privileged access to applications, machines, and services through local Edge Backends.
-
Design highly available, observable, and resilient distributed systems using modern cloud-native technologies.
-
Mentor engineers, lead architecture discussions, and drive engineering best practices.
-
Leverage AI-assisted software development throughout the SDLC to improve productivity, code quality, testing, documentation, and operational excellence.
-
Build platform capabilities to discover, govern, and secure AI agents, automation frameworks, MCP servers, and agentic applications.
-
Develop scalable services supporting AI-native enterprise workloads.
-
Follow AI SDLC best practices across design, implementation, testing, deployment, and operations.r
AI & Agentic Engineering
WHAT YOU BRING
-
1+ years at a Associate Principal level of backend software engineering experience.
-
Expert-level Go (Golang) development.
-
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.
-
Experience building enterprise security, IAM, PAM, Zero Trust, or networking products is highly desirable.
-
Hands-on experience using AI-assisted development tools such as GitHub Copilot, Cursor, Claude Code, Windsurf, ChatGPT, or similar.
-
Understanding of modern AI application architectures, including LLMs, RAG, AI Agents, orchestration frameworks, and Model Context Protocol (MCP).
-
Familiarity with AI SDLC best practices, including AI-assisted development, automated testing, secure coding, CI/CD automation, observability, and responsible use of AI-generated code.
-
Strong technical leadership, architecture, mentoring, and communication skills.