Software Engineer - Agentic

About XageCyberattacks on critical infrastructure, government, and private enterprises are at an all time high – and only growing more urgent with AI. Xage is a global leader in zero trust access and protection at the forefront of solving this pressing issue. We are pioneering a secure tomorrow by empowering organizations worldwide to connect anyone to anything, while delivering unparalleled defense against every cyber threat.We have built tremendous momentum across governments and commercial enterprises around the world, and it’s just the beginning. Recognized by Forbes as one of America’s Best Startup Employers, Xage prioritizes creativity, collaboration, and innovation in pursuit of our mission.We are headquartered in Palo Alto, CA and have global teams across North America, EMEA, and APJ.We’re passionate about solving problems that have positive, real-world consequences for the lives of everyday people. We hope you’ll join us in the fight against cyberattacks and safeguarding critical systems.About the RoleWe are seeking an experienced and visionary Senior Software Engineer to design and build our next-generation Zero Trust for Agentic AI platform. As AI agents evolve from sandboxed pilots into autonomous systems capable of executing real-world actions, invoking APIs, and accessing sensitive databases across hybrid cloud and operational technology (OT) environments, security must evolve with them.In this role, you will build the critical security fabric that moves past simple prompt/output monitoring and into deterministic runtime visibility and control. You will engineer the gateways, proxies, and identity management systems that protect autonomous AI agents, Large Language Models (LLMs), and enterprise resources from prompt injection, rogue behavior, data leakage, and privilege escalation.Key ResponsibilitiesArchitect AI Gateways & Sentries: Design and develop the runtime components (like Xage Agent Sentry and Resource Gateway) to encapsulate AI agents, intercepting and inspecting inputs, outputs, tool calls, and API interactions.Implement Deterministic Access Controls: Build jailbreak-proof, identity-based permissioning models and agent entitlements to enforce strict least-privilege access across APIs, SaaS applications, Model Context Protocol (MCP) servers, and databases.Analyze Behavioral Anomalies: Build intelligent monitoring systems that establish a baseline for normal agent behavior and leverage ML to flag deviations, catching rogue agent actions or privilege escalation attempts before they hit critical infrastructure.Develop Agent Identity Management: Create robust, centralized frameworks for agent registration, lifecycle management, and automated credential rotation to eliminate hardcoded secrets and shared service account vulnerabilities.Build End-to-End Visibility Pipelines: Engineer high-throughput, tamperproof logging mechanisms to capture and audit every prompt, action, tool call, and resource access for comprehensive governance.Scale a Distributed Security Fabric: Ensure security controls deploy seamlessly across multi-cloud, on-premises, and edge/OT environments via a unified, resilient platform.Required Skills and QualificationsTechnical RequirementsBackend & Systems Engineering: 3-5+ years of experience building high-performance, distributed, and scalable enterprise software (preferred languages: Go, Python, C or C++).Machine Learning & AI Security: Strong hands-on experience deploying ML models in production environments. Familiarity with NLP, LLM alignment/guardrails (e.g., Llama Guard, NeMo Guardrails), and implementing low-latency inference at the proxy/gateway level.AI/LLM Integration & Protocols: Deep understanding of the Agentic AI lifecycle, tool-calling mechanisms, and emerging integration protocols like MCP (Model Context Protocol) and REST APIs.Security & Zero Trust Architecture: Solid foundation in application security, API gateway design, proxy architectures (e.g., Envoy), identity access management (IAM), and credential management/rotation.Infrastructure & Edge: Experience with containerization (Docker, Kubernetes) and deploying applications across hybrid environments (Cloud, SaaS, and Edge/OT).Soft Skills & ExperienceExperience in cybersecurity product development, specifically in AI Security (Securing LLMs/Agents, prompt injection mitigation) is highly preferred.Strong systems-level thinking with the ability to build predictive boundaries around dynamic, runtime AI behaviors.Strong communication skills to collaborate with AI researchers, security analysts, and enterprise architecture teams.Key Business Impacts You Will DeliverEnable High-Stakes AI Deployment: Turn risky, sandboxed AI experiments into secure, production-ready enterprise tools.Mitigate Modern Threats: Directly block harmful agent behaviors and data exfiltration before they impact the business.Simplify AI Complexity: Provide enterprises with a “single pane of glass” view to trust, govern, and audit their autonomous AI workforces.Location: Palo Alto, CASalary Range: $140K - $190K