Senior Staff Software Engineer - Identity Governance

Ping Identity•Austin, TX

14h•Hybrid

About The Position

The Ping Identity Data Platform team is building the next generation of enterprise AI governance capabilities to enable secure, scalable, and responsible adoption of AI agents. The team is evolving governance frameworks, platforms, and operational processes to manage AI agents across the enterprise, addressing key areas such as security, compliance, identity, risk management, and responsible AI. As part of our data platform team, you will help define and implement capabilities for agent discovery, lifecycle governance, policy enforcement, observability, and secure integration of AI agents, tools, MCP servers, and enterprise resources. You will work on taking governance concepts from design to reality in a fast-paced, collaborative, cross-functional environment, partnering with engineering, security, compliance, and product teams to shape the future of AI adoption.

Requirements

Bachelor's degree in Computer Science, Software Engineering, or equivalent practical experience.
8+ years of experience in Java application development.
Strong proficiency in Java and object-oriented design principles.
Experience building scalable, distributed, and resilient applications.
Strong experience with Gradle for dependency management, build automation, project configuration, and optimizing build processes while troubleshooting dependency conflicts and build-related issues in large-scale software projects.
Good understanding of performance profiling, JVM tuning, memory management, and application optimization.
Experience troubleshooting dependency issues and optimizing application performance.
Strong knowledge of concurrent programming, multithreading, and synchronization.
Experience with debugging using logs, thread dumps, heap dumps, and profiling tools.
Familiarity with software design patterns, automated testing, and system integration.
Strong problem-solving, communication, and technical leadership skills.

Nice To Haves

Exposure to Identity Governance (IGA) concepts
Experience building MCP servers and AI agents using popular frameworks such as LangGraph and LlamaIndex.
Experience with cloud platforms such as AWS, Azure, or Google Cloud.
Experience with containerization and orchestration technologies such as Docker and Kubernetes.
Experience with CI/CD pipelines and DevOps practices.
Experience building enterprise-scale distributed systems.
Experience mentoring engineers and leading technical initiatives.

Responsibilities

Design, develop, and maintain AI agent governance capabilities across AI platforms like Amazon Bedrock, Google Vertex AI, Microsoft Copilot, Azure AI Foundry etc.
Rapidly prototype and iterate on AI agent capabilities, continuously evaluating and adopting new frameworks, features, and industry best practices as the AI ecosystem evolves.
Leverage AI coding assistants and agentic development tools to accelerate delivery while maintaining a strong focus on clear requirements, modular design, observability, maintainability, and code quality.
Drive the evolution of core Identity Governance capabilities—including certifications, lifecycle management, workflows, and Separation of Duties (SoD)—by enhancing existing functionality, improving performance and scalability, and delivering incremental features that strengthen enterprise identity governance.
Partner closely with Support and customer-facing teams to troubleshoot and resolve customer issues, drive timely solutions, improve product reliability, and deliver a positive customer experience that builds trust and customer delight.
Monitor AI agent performance, usage, operational health, and security across multiple platforms.
Collaborate with platform, security, and product teams to implement secure AI solutions using authentication, authorization, and least-privilege principles.
Contribute to observability by implementing logging, metrics, monitoring, and compliance for AI agents.
Evaluate and adopt emerging AI agent platforms, interoperability standards (such as MCP and Agent-to-Agent communication), and governance technologies.
Document architecture, governance processes, operational procedures, and engineering best practices for AI agents.