Jobs at Saviynt

The AI Platform Engineer will own distributed training and inference operations using Ray on GPUs, manage the lifecycle of machine learning models, optimize performance, and integrate reinforcement learning. Key responsibilities include overseeing the Ray ecosystem, configuring training and inference systems, and ensuring quality and performance metrics are met throughout the model lifecycle.

Lead the design, development, and implementation of AI security products. Collaborate across teams, drive engineering processes, and maintain existing services. Influence product direction and act as a technical expert.

The Principal Software Engineer will design, implement, and lead AI security product development, focusing on scalable software solutions across cloud platforms and driving engineering best practices.

Define and drive reliability for Saviynt's SaaS platform by designing, building, and operating scalable, reusable platform services. Lead Kubernetes platform engineering, multi-region cloud architectures, event-driven systems, CI/CD pipelines, observability, service mesh, and shared relational data services. Provide tooling, APIs, on-call support, and cross-team guidance.

Design, build, and operate shared, highly available platform services (Kubernetes, cloud, messaging, CI/CD). Develop automation and APIs (primarily in Go/Python), implement observability, service mesh, and multi-region solutions, and support on-call rotations to ensure platform reliability and scalability for internal consumers.

Serve as the primary HR strategist for Americas Sales and Marketing: align people strategy to revenue goals, partner with Finance/RevOps on territory and incentives, lead org design and re-orgs, manage pay/performance and quota alignment, drive L&D and TA collaboration, use HR metrics for insight, and coach managers on complex employee relations.

Lead design and implementation of shared, highly available cloud platform services: Kubernetes platforms, CI/CD, event-driven messaging, observability, service mesh, relational DB as-a-service, automation in Go/Python, multi-region cloud optimizations, and on-call support.

The role involves leading quality assurance initiatives for Saviynt's AI-powered identity platform, managing multiple testing types, and collaborating on product quality enhancements in a fast-paced environment.

Design, implement, and release workflows for AI security products. Collaborate across platforms, utilizing cloud and AI technologies. Act as a technical expert, driving process improvement and supporting application development.

Lead the end-to-end vision and architecture for a governed, multi-tenant data platform: design real-time ingestion and streaming, transformation and storage for mixed workloads, unified access and tenant isolation, observability and governance, cost controls, and organizational standards. Drive benchmarks, cloud choices, security compliance, and mentor senior engineers while guiding multi-year, company-wide adoption.

Drive regional enterprise sales for Saviynt's cloud identity, access governance, and PAM solutions. Manage full sales cycle from prospecting through POC, collaborate with SE and product teams, build pipeline via partners and outbound efforts, meet quota, maintain SFDC records, and support sales/marketing events.

The Associate Principal SDET will lead the development of automation frameworks, driving AI-powered testing strategies and ensuring software quality across platforms while mentoring global teams.

The Principal Software Engineer will lead the Connectors team in designing scalable frameworks for integrating enterprise applications, mentoring engineers, and resolving complex technical challenges.

As a Technical Program Manager, you'll oversee project deliverables, facilitate cross-functional development, manage schedules, communicate with management, and drive technical initiatives. You need strong agile experience and technical knowledge.

The Principal Software Engineer leads the architectural design of a data platform, ensuring isolated and compliant data flows, overseeing AI data lakes, batch and streaming pipelines, and developing service APIs.

Design, build, and operate cloud and distributed Edge infrastructure and deployment automation. Implement CI/CD, release orchestration, observability, secrets and certificate management, and resilient architectures. Integrate AI-assisted engineering and support AI-native, agentic workloads while ensuring scalability, reliability, security, and disaster recovery.

Design and build native endpoint agents for Windows, macOS, and Linux to enforce privileged endpoint device management, collect local telemetry, detect unauthorized or agentic workloads, secure agent-backend communication, and optimize performance. Lead architecture, mentor engineers, and apply AI-assisted development and AI SDLC practices to discover and govern AI agents on enterprise endpoints.

Architect and build a scalable AI Security platform: develop Go microservices for Cloud Control Plane and distributed Edge Backends, design resilient policy sync, discovery and access-brokering services, ensure high availability and observability, and provide technical leadership and mentoring.

Design and implement scalable, resilient cloud and edge microservices in Go for an AI-focused identity and privileged access platform. Build cloud control plane and distributed edge backends, ensure secure policy synchronization and discovery, integrate AI-native features, mentor engineers, and drive architecture and engineering best practices.

Own Marketing’s reporting and analytics layer by building executive dashboards, defining KPIs, modeling data across GTM systems, and establishing governance and trusted sources of truth. Partner cross-functionally to measure funnel performance, attribution, campaigns, pipeline, and ROI. Help evaluate and develop AI-powered analytics, conversational reporting, automated insights, and intelligent visualization while translating complex data into actionable recommendations for leadership.