Principal Engineer - Agentic AI Systems
About Saviynt
Saviynt’s Enterprise Identity Cloud helps modern enterprises scale cloud initiatives and solve the toughest security and compliance challenges in record time. The company brings together identity governance (IGA), granular application access, cloud security, and Privileged Access Management (PAM) to secure the entire business ecosystem and provide a frictionless user experience. The world’s largest brands trust Saviynt to accelerate digital transformation, empower distributed workforces, and meet continuous compliance. We are a distributed global R&D team that is extremely focused on building a platform that solves the toughest security and compliance challenges while helping Saviynt maintain its leadership position in delivering enterprise identity cloud solutions.
About the Role
We are seeking a visionary Principal Engineer to lead the architecture and development of next-generation Agentic AI systems for Saviynt’s Enterprise Identity Cloud. This role is ideal for a hands-on technical leader who thrives at the intersection of AI/LLMs, scalable cloud systems, and enterprise security. You will design and deliver production-grade multi-agent AI workflows leveraging LLMs, orchestration frameworks, and observability tools, while also mentoring a high-caliber engineering team.
What You’ll Do
Architecture & Development
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Design multi-agent AI workflows for complex identity and governance scenarios.·
Architect autonomous planning/execution systems that translate natural language into secure workflows.·
Build scalable, fault-tolerant microservices with Kubernetes + HPA for enterprise deployments.·
Implement observability frameworks (metrics, traces, logs) to monitor agentic AI systems.·
Ensure security, compliance, and auditability in AI workflows.LLM Engineering
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Fine-tune and optimize LLMs (GPT, Claude, Llama) for enterprise identity use cases.·
Implement RAG, few-shot, and advanced prompting strategies.·
Build cost-efficient, low-latency inference pipelines using AWS Bedrock and Azure OpenAI.·
Maintain robust model versioning, evaluation, and A/B testing frameworks.Cloud & Systems
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Lead multi-cloud AI deployments (AWS, Azure).·
Architect real-time collaboration between human users and AI agents.·
Build secure service mesh and message queues (Istio, Kafka, RabbitMQ).·
Ensure enterprise-grade high availability, disaster recovery, and scaling.Leadership
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Lead and mentor a team of 5-6 AI/ML and backend engineers.·
Establish technical standards, coding practices, and design reviews.·
Drive roadmaps and research initiatives in partnership with product and business teams.·
Foster a culture of innovation, experimentation, and operational excellence.What You Bring
Required
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12+ years software engineering experience, with 5+ years in large-scale enterprise platforms.·
3+ years building LLM/AI-driven systems, ideally with multi-agent orchestration.·
Strong proficiency in Python and AI frameworks (LangChain, LangGraph, Transformers).·
Expertise in containerized deployments (Docker, Kubernetes, Helm) with HPA scaling.·
Proven experience with observability stacks·
Hands-on experience with AWS Bedrock and Azure AI services.·
Track record of technical leadership and mentoring in distributed teams.Preferred
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Advanced degree in Computer Science, AI, or related field.·
Knowledge of vector databases, semantic search, and knowledge graphs.·
Experience with enterprise compliance requirements.·
Prior contributions to open-source AI frameworks.Tech Stack You’ll Work On
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Languages: Python, Java·
AI Frameworks: Bedrock, LangChain, LangGraph, Transformers,·
Cloud & AI Providers: AWS Bedrock, Azure OpenAI, Anthropic·
Databases: PostgreSQL, Redis·
Infra & Observability: Kubernetes, HPA, Grafana·
Messaging: Kafka, RabbitMQWhy Join Us?
At Saviynt, you’ll be pioneering agentic AI at enterprise scale, solving real-world security and compliance challenges for Fortune 500 companies. You’ll have the autonomy to experiment with emerging AI technologies while leading a team of innovators in one of the fastest-growing areas of enterprise software.
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