The Challenge

Enterprises need dependable visibility into both the data they hold and the AI they use. OneTrust’s Detection & Discovery team owns and actively maintains Data Discovery and Data Catalog capabilities while expanding discovery of AI models, agents, and related cloud resources. Customers rely on these systems to find, understand, and govern assets across complex environments.

This role is intentionally balanced between strengthening the Data Discovery and Data Catalog pipeline and advancing AI Detection & Discovery. You will provide hands-on technical leadership across both: sustaining and improving mature production capabilities while building the next generation of AI discovery.

Your Mission

Data Discovery & Data Catalog

• Own the technical evolution and ongoing maintenance of Data Discovery and Data Catalog services and modules, including production support for capabilities customers depend on.

• Lead a major engineering-quality initiative to reduce technical debt, address critical issues, and modernize the code and architecture without compromising customer stability.

• Improve the stability, reliability, performance, and operability of the end-to-end discovery and catalog pipeline, from scanning and ingestion through cataloging and downstream use.

• Identify and deliver practical opportunities to apply AI across discovery and catalog workflows, improving automation and customer value where it makes sense.

AI Detection & Cloud Discovery

• Design and build Java services, APIs, and reusable connectors that discover AI models, agents, and related resources across cloud and AI platforms.

• Translate provider APIs, identity models, and resource structures into secure, consistent discovery contracts and normalized inventory data.

• Advance continuous, scheduled, and incremental discovery so changes to discovered assets are reflected accurately and promptly.

• Enable secure discovery across customer accounts, projects, subscriptions, and regions, and partner with AI Governance teams on asset and lifecycle integrations.

Production Support & Reliability

• Participate in customer-facing production-support calls for Data Discovery and AI Governance, including issues involving customer-managed or on-premises components.

• Troubleshoot complex issues across Java services, Linux environments, Kubernetes deployments, cloud integrations, and network connectivity; partner with Support, Operations, and engineering teams to mitigate customer impact.

• Drive incidents from investigation through root cause and durable corrective action, using findings to improve product stability, supportability, and documentation.

Technical Leadership

• Set architecture and lead multi-quarter initiatives from design through production adoption; make pragmatic build-versus-reuse decisions.

• Establish a high bar for code quality, design reviews, automated testing, and production readiness.

• Improve observability and operational maturity; use incident patterns and operational metrics to drive systemic improvements.

• Collaborate with Product, UX, Security, Platform, and customer-facing teams; mentor engineers and influence practices beyond your immediate projects.

You Are

A hands-on technical leader who can balance investment in new capabilities with stewardship of mature, business-critical software. You bring sound judgment to complex systems, work comfortably across architecture and implementation, and help teams deliver improvements without losing sight of reliability and customer impact.

Your Experience Includes

• 12+ years of professional software engineering experience, including substantial hands-on development in Java and the Spring ecosystem.

• A track record of designing and delivering distributed, cloud-native services and APIs used in production at enterprise scale.

• Experience owning and evolving production software, including technical-debt reduction, critical issue resolution, and improvements to stability and reliability.

• Hands-on experience debugging production services in Linux and Kubernetes environments.

• Working knowledge of networking and connectivity troubleshooting, including DNS, TLS, HTTP, and proxy or firewall paths.

• Experience building integrations with external platforms, including provider APIs, authentication and authorization, pagination, data mapping, and evolving API behavior.

• Strong knowledge of distributed systems and workflow or event-driven architectures, including failure handling, retries, idempotency, and observability.

• Experience designing secure, multi-tenant SaaS systems, including tenant isolation and secure service-to-service communication.

• Demonstrated ability to lead technical strategy across teams, guide architecture decisions, and deliver complex initiatives while remaining effective in code and design reviews.

• A bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Extra Awesome

• Experience with data discovery, data catalog, scanning, ingestion, or asset-inventory platforms.

• Experience applying AI or machine learning to discovery, data, or catalog workflows.

• Experience with AI platforms and infrastructure, including discovery of models, agents, runtimes, tools, or related cloud resources.

• Hands-on experience with AWS, Azure, or Google Cloud APIs and identity models; familiarity with Amazon Bedrock / AgentCore, Azure AI Foundry, or Vertex AI.

• Experience with Java workflow orchestration frameworks such as Temporal, connector frameworks, or developer automation.

• Experience with Kafka or other messaging technologies, CI/CD, and production operations for cloud-native services.

• Familiarity with AI governance, security, privacy, compliance, or other regulated enterprise domains.