

You will play a critical role in building a multi-tenant PaaS for ML pipelines and inference, ensuring scalability, reliability, and security. You will take ownership of critical platform components, drive best practices, and mentor other engineers.
Background in MLOps, Data Platforms, or Machine Learning workflows.
Experience with additional monitoring and logging tools (CloudWatch, Prometheus, ELK).
Leadership experience in scaling cloud-native platforms.
Experience in information security – an advantage
Understanding of identity & access management, secrets management, or zero-trust architecture - Bonus.
משרות נוספות שיכולות לעניין אותך

What you need to succeed:
The salary range for this position is $150,000 – $250,000/year, plus commissions or discretionary bonus, which will be based on the employee’s performance. Base pay may also vary considerably depending on job-related knowledge, skills, and experience. The compensation package includes a wide range of medical, dental, vision, financial, and other benefits.

In this role, you will take part in building a new innovative product, and have a huge influence on its design, flows, and technology.
In this role, you must demonstrate high professional skills, fast technology adoption, and the ability to work on AWS.
Responsibilities:

Responsibilities

CyberArk is looking for an experienced Staff Software Engineer for our new Authentication service. You will be responsible for building this core SaaS service, built on-top of AWS using .NET, EKS, Terraform and other cloud technologies. You will be working with an elite team to produce top-notch services at the highest standards, meeting the high security, stability, and performance standards of the largest enterprises in the world.

In this role you will be using AWS serverless architecture, AWS CDK & Python to design, develop, test, secure & deploy services from planning to production. You will practice all software development life cycle in an agile oriented environment while exploring new technologies and tools to keep us using cutting edge solutions.
• Bachelor’s Degree in Computer Science or Engineering related field / technology Elite unit alumni with relevant experience
• 5+ years of experience in Python / Go / Java / Node/ C++
• 2+ ofexperience in developing and deploying modular cloud-based systems on
AWS
• Proven experience with creating architecture for cloud-based systems, considering scalability, security, and performance
• Have experience leading the design, development and delivery of features in SaaS applications
• Participate in continuous and iterative engineering cycles with emphasis on code quality, supportability, scalability, and performance
• Be passionate about code design, high-quality code, and code reviews, optimizing and challenging the status quo
• An independent, proactive nature, coupled with an internal drive for excellence and improvement
• Explore new technologies and tools to keep us using cutting edge solutions
• Passionate about code design, high-quality code, and code reviews, optimizing and challenging the status quo
• A thorough and methodical approach to any task, with the ability to plan, conduct, prioritize, track, and measure processes
• Excellent communication skills and the ability to coach others
• Proactive by nature; internal drive for excellence and improvement
• Experience with AWS serverless architecture and AWS CDK.
• Experienced with modern CI/CD tools, in particular, GitHub, Jenkins, and Artifactory
• Experience in enterprise scale application development in cloud/SaaS environment (AWS serverless architecture is a definite advantage)
• Good understanding of security and networking implementation and best practices

We’re building foundational infrastructure to secure AI agents — including their identities, access patterns, and interactions with sensitive systems and data. This includes designing intelligent, dynamic mechanisms for ephemeral access control, secrets management, and agent/user identity tailored to modern agent frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, and beyond.
You’ll help define how agents (both machine and human-facing) authenticate, receive scoped access, perform actions securely, and leave behind a verifiable audit trail.
Responsibilities:
Develop secure, scalable Python services to support agent identity, secrets access, credential management, and authorization flows.
Implement JWT-based agent/user authentication, and real-time policy checks based on agent context and tool usage.
Build SDKs, wrappers, and tool integrations that enable popular agent frameworks (LangChain, LangGraph, Semantic Kernel, etc.) to securely request and use secrets.
Collaborate closely with the architect and other engineers to design components with clear boundaries and clean contracts.
Ensure secrets and credentials are injected only when needed, redacted from logs, and never persist in agent memory or prompts.
Write thorough tests and maintain high-quality, well-documented code.
Work cross-functionally with internal platform, AI, and security teams to understand requirements and refine implementation plans.
5+ years of backend or systems development experience, primarily in Python.
Strong understanding of secure API development, authentication models (JWT, OAuth2), and basic access control patterns.
Exposure to secrets management platforms (AWS Secrets Manager, CyberArk Conjur, etc.) - bonus.
Familiarity with or strong interest in AI agent frameworks (LangChain, AutoGen, LlamaIndex, etc.).
Exposure to identity and access management concepts — especially in zero-trust or dynamic runtime environments — is highly valuable.
Experience building SDKs or developer-focused tools is a plus.
A security-first mindset, attention to detail, and strong debugging/testing skills.
Excellent communication and collaboration skills — you’ll be interfacing with multiple engineering groups to deliver complete and secure solutions.

You will play a critical role in building a multi-tenant PaaS for ML pipelines and inference, ensuring scalability, reliability, and security. You will take ownership of critical platform components, drive best practices, and mentor other engineers.
Background in MLOps, Data Platforms, or Machine Learning workflows.
Experience with additional monitoring and logging tools (CloudWatch, Prometheus, ELK).
Leadership experience in scaling cloud-native platforms.
Experience in information security – an advantage
Understanding of identity & access management, secrets management, or zero-trust architecture - Bonus.
משרות נוספות שיכולות לעניין אותך