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Ping Identity is seeking a Staff Software Engineer to join the Data Platform team, which is building next-generation enterprise AI governance capabilities. The role focuses on enabling secure, scalable, and responsible adoption of AI agents across enterprises, addressing security, compliance, identity, risk management, and responsible AI.
You will design and implement capabilities for agent discovery, lifecycle governance, policy enforcement, observability, and secure integration of AI agents, tools, MCP servers, and enterprise resources. This is a fast-paced, collaborative position partnering with engineering, security, compliance, and product teams.
Key responsibilities include:
- Design, develop, and maintain AI agent governance capabilities across platforms like Amazon Bedrock, Google Vertex AI, Microsoft Copilot, and Azure AI Foundry
- Rapidly prototype and iterate on AI agent capabilities, evaluating new frameworks and industry best practices
- Leverage AI coding assistants and agentic development tools 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
- Partner with Support and customer-facing teams to troubleshoot issues and improve product reliability
- Monitor AI agent performance, usage, operational health, and security across platforms
- Implement secure AI solutions using authentication, authorization, and least-privilege principles
- Contribute to observability through logging, metrics, monitoring, and compliance implementation
- Evaluate emerging AI agent platforms and interoperability standards like MCP
- Document architecture, governance processes, 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
