Saviynt
Identity Security
SeniorSoftwareEngineer(AgenticAI)
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Software Engineer (Agentic AI) at Saviynt. Skills: Agentic AI, LLMs, Orchestration frameworks, Scalable products, Microservices, APIs, Kubernetes, HPA, Observability, Foundation models, RAG, Prompt engineering, AWS Bedrock, Azure OpenAI, Multi-cloud environments, Kafka, RabbitMQ, Istio. Developing, optimizing, and deploying AI-driven solutions. Building scalable products that leverage LLMs and orchestration frameworks”
What You'll Achieve.
Safeguard digital assets; Drive operational efficiency; Reduce compliance costs; Enhance system reliability and compliance; Deliver high-quality, secure, and observable systems
Industry & Context.
Complete security & privacy literacy and awareness training during onboarding and annually thereafter, Review (initially and annually thereafter), understand, and adhere to Information Security/Privacy Policies and Procedures
What They're Looking For.
Must Have
5–8 years of software engineering experience, at least 2 years in AI/ML or large-scale enterprise systems, Strong programming skills in Python, experience with AI/ML frameworks (LangChain, LangGraph, Transformers), Hands-on experience in developing containerized applications (Docker, Kubernetes), Exposure to observability frameworks (Prometheus, Grafana, ELK), Experience working with cloud services such as AWS and/or Azure, Good understanding of scalable systems, HPA, and secure coding practices
Nice to Have
Experience with AWS Bedrock or Azure OpenAI services, Knowledge of vector databases and semantic search, Familiarity with Kafka, RabbitMQ, or service mesh (Istio), Contributions to open-source AI or cloud projects
What You'll Do.
and deploying AI-driven solutions
Building scalable products that leverage LLMs and orchestration frameworks
Delivering high-quality
and observable systems in a multi-cloud environment
Contribute to the design and implementation of multi-agent AI workflows
Develop microservices and APIs with focus on scalability and resilience using Kubernetes and HPA
Implement observability (metrics
logs) into all deployed systems
Collaborate with architects and principal engineers to enhance system reliability and compliance
Work with foundation models (GPT
Llama) to build domain-specific AI features
Apply RAG and prompt engineering techniques for enterprise identity use cases
Contribute to the development of cost-efficient inference pipelines with AWS Bedrock and Azure OpenAI
Develop and deploy solutions in multi-cloud environments (AWS
Integrate with secure messaging and orchestration systems (Kafka
Ensure systems follow security
and enterprise audit requirements
How You'll Work.
Team & Collaboration
Close collaboration with cross-functional teams; Collaborate with architects and principal engineers; Participate in code reviews, knowledge sharing, and team discussions
Full Job Description
## Description Saviynt's AI-powered identity platform manages and governs human and non-human access to all of an organization's applications, data, and business processes. Customers trust Saviynt to safeguard their digital assets, drive operational efficiency, and reduce compliance costs. Built for the AI age, Saviynt is today helping organizations safely accelerate their deployment and usage of AI. Saviynt is recognized as the leader in identity security, with solutions that protect and empower the world’s leading brands, Fortune 500 companies and government institutions. For more information, please visit www.saviynt.com. We are looking for a highly skilled and motivated Software Engineer to join our Agentic AI team within Saviynt’s Enterprise Identity Cloud. You will work on developing, optimizing, and deploying AI-driven solutions, focusing on building scalable products that leverage LLMs and orchestration frameworks. The role involves hands-on development, close collaboration with cross-functional teams, and delivering high-quality, secure, and observable systems in a multi-cloud environment. ## What You’ll Do Architecture & Development: Contribute to the design and implementation of multi-agent AI workflows. Develop microservices and APIs with strong focus on scalability and resilience using Kubernetes and HPA. Implement observability (metrics, traces, logs) into all deployed systems. Collaborate with architects and principal engineers to enhance system reliability and compliance. LLM Engineering:Work with foundation models (GPT, Claude, Llama) to build domain- specific AI features.·Apply RAG and prompt engineering techniques for enterprise identity use cases.·Contribute to the development of cost-efficient inference pipelines with AWS Bedrock and Azure OpenAI.Cloud & Systems·Develop and deploy solutions in multi-cloud environments (AWS, Azure).Integrate with secure messaging and orchestration systems (Kafka, RabbitMQ, Istio).·Ensure systems follow
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