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Ping Identity's Data Platform team is building next-generation enterprise AI governance capabilities to enable secure, scalable, and responsible adoption of AI agents across organizations. As a Staff Engineer, you will design and implement core capabilities for agent discovery, lifecycle governance, policy enforcement, observability, and secure integration of AI agents, tools, and enterprise resources.
Key responsibilities include:
- Design, develop, and maintain AI agent governance capabilities across major platforms (Amazon Bedrock, Google Vertex AI, Microsoft Copilot, Azure AI Foundry)
- Rapidly prototype and iterate on AI agent capabilities, evaluating new frameworks and industry best practices as the AI ecosystem evolves
- Leverage AI coding assistants and agentic development tools to accelerate delivery while maintaining focus on clear requirements, modular design, observability, and code quality
- Drive evolution of core Identity Governance capabilities including certifications, lifecycle management, workflows, and Separation of Duties (SoD)
- Partner with Support and customer-facing teams to troubleshoot issues, drive timely solutions, and improve product reliability
- 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
- Implement logging, metrics, monitoring, and compliance for AI agents
- Evaluate and adopt emerging AI agent platforms and interoperability standards (MCP, Agent-to-Agent communication)
- Document architecture, governance processes, operational procedures, and engineering best practices
Required qualifications:
- Bachelor's degree in Computer Science, Software Engineering, Data Engineering, or equivalent practical experience
- 8+ years in data engineering-related software engineering roles with hands-on experience in data ingestion, preparation, processing, and building scalable data pipelines
- Experience with Apache Spark, Apache Beam, or Apache Flink
- Strong understanding of data modeling and designing scalable data solutions for enterprise applications
- Extensive experience with BigQuery, SQL, NoSQL databases, and Elasticsearch
- Experience designing, optimizing, and troubleshooting analytical queries
- Hands-on experience building and maintaining ETL pipelines and large-scale data processing solutions
- Familiarity with structured and unstructured data management concepts
- Understanding of distributed data systems and data integration patterns
- Strong analytical, problem-solving, and communication skills
