Staff Software Engineer, Machine Learning

About Ping Identity:

At Ping Identity, we believe in making digital experiences both secure and seamless for all users, without compromise. We call this digital freedom. And it's not just something we provide our customers. It's something that inspires our company. People don't come here to join a culture that's built on digital freedom. They come to cultivate it.

Our intelligent, cloud identity platform lets people shop, work, bank, and interact wherever and however they want. Without friction. Without fear.

While protecting digital identities is at the core of our technology, protecting individual identities is at the core of our culture. We champion every identity. One of our core values, Respect Individuality, reminds us to celebrate differences so you are empowered to bring your authentic self to work.

We're headquartered in Denver, Colorado and we have offices and employees around the globe. We serve the largest, most demanding enterprises worldwide, including more than half of the Fortune 100. At Ping Identity, we're changing the way people and businesses think about cybersecurity, digital experiences, and identity and access management.

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.

You Will:

Design, develop, and maintain AI agent governance capabilities across AI platforms like Amazon Bedrock, Google Vertex AI, Microsoft Copilot, Azure AI Foundry etc.

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.

Ensure Ops readiness and observability for the features shipped, by implementing logging, metrics, monitoring, and alerts.

Document architecture, governance processes, operational procedures, and engineering best practices for AI agents.

You Have:

Bachelor's degree in Computer Science, Software Engineering, ML Engineering , or equivalent practical experience.

Hands-on coding experience in developing enterprise and cloud applications using Java and Python

6+ years of experience in ML Engineering- related software engineering roles, with hands-on experience in ML algorithms such as FP-Growth , techniques such as Market Basket Analysis, data ingestion, data preparation, data processing, and building scalable data pipelines using frameworks such as Apache Spark, Apache Beam, or Apache Flink.

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.

Good understanding of distributed data systems and data integration patterns.

Strong analytical, problem-solving, and communication skills.