Senior Staff Software Engineer - AI Governance

Job Description

Job Description

Strength in Trust 

OneTrust's mission is to enable innovation through the responsible use of data and AI. We believe that ensuring data is trusted shouldn't slow teams down—it should accelerate what's possible. This led us to develop the first technology platform for responsible data use in 2016. Today, with AI representing the latest and most impactful expansion of data yet, OneTrust is once again redefining what responsible innovation looks like. OneTrust, the AI‑Ready Governance Platform™, unifies regulatory intelligence, automation, and connected governance workflows so businesses can continue to move at the speed of AI while ensuring good governance to prevent data misuse at scale. Trusted by thousands of organizations worldwide, OneTrust is shaping the future where trusted data becomes a transformative force for business and society. 

As a Senior Staff Software Engineer, you will serve as a technical leader for OneTrust's AI Governance (AIG) platform, driving the design, scalability, and reliability of systems that enable enterprises to deploy and govern AI and LLM-powered applications responsibly. You will deeply understand how customers build, deploy, and operate AI systems, and translate those needs into secure, compliant, and observable platform capabilities.  

Development 

• Lead the design and development of Java/Python microservices and shared libraries integrating with AI platforms for OneTrust's AI Governance product.
• Design, build, and test cloud-native applications deployed on Microsoft Azure using Core Java, REST, and the Spring ecosystem.
• Lead the architecture and development of reusable AIG reporting and dashboard capabilities that integrate governance data from SQL databases and analytical platforms with runtime observability signals.
• Design reusable semantic-layer and metric-abstraction capabilities, including dataset contracts, metric definitions, query APIs, pre-aggregation, caching, filtering, time-period selection, and drill-down workflows.
• Lead event-driven integrations using Kafka and Apache Flink to consume normalized observability events and produce dashboard-ready datasets and derived metrics.
• Integrate with the AI Observability platform through well-defined APIs and data contracts for runtime metrics, logs, traces, alerts, policy decisions, and evidence.
• Own technical design for critical systems, ensuring scalability, security, and reliability.
• Partner with frontend engineers to build reusable dashboard shells, visualization components, filters, data tables, and entity drill-down experiences.
• Maintain strong automated unit and integration test coverage in line with team standards. 

Collaboration

• Work closely with UX, Product Managers and/or Product Owners, as well as other developers to contribute to planning and grooming sessions and drive team discussions on system architecture and component design.   
• Partner with Product, UX, and Customer Success to understand customer AI use cases and governance needs.
• Lead architecture discussions and technical planning.
• Drive alignment across teams on platform design and priorities.
• Contribute to sprint planning and delivery.  

Support

• Reduce defects by identifying and addressing issues early in the development lifecycle.
• Ensure critical and high-priority CII's are delivered per SLA.   
• Promote early defect detection through strong design and testing.
• Improve system monitoring, resilience, and operational maturity.  

Code Review

• Set standards for clean, secure, and maintainable code.
• Conduct thorough reviews for distributed and AI-enabled systems.
• Guide engineers on testing, automation, and AI system validation. 

Lead

• Help build high-performing teams by mentoring the team on new technical skills. 
• Influence technical strategy and long-term platform direction.
• Build a culture of ownership, learning, and engineering excellence.  
• Lead multi-quarter technical roadmaps across teams and make practical build-versus-reuse decisions. 

A senior technical leader with strong system design and hands-on execution skills, who understands how enterprises use AI and LLMs in real-world workflows and can translate those needs into scalable, secure, and compliant platform solutions.  

Your Experience Includes     

• Bachelor's or master's degree in computer science, Engineering, or a related technical or business field.
• 12+ years of professional software engineering and development experience.
• Strong expertise in Java/J2EE, Spring, Python, design patterns, microservices, and cloud-native distributed systems.
• Proven experience leading reusable platform, reporting, analytics, or data products that support multiple teams or dashboards.
• Hands-on experience with Cube.js, semantic layers, metric layers, or comparable metric/query abstraction systems.
• Hands-on experience with Apache Flink for real-time stream processing, windowed aggregation, event correlation, or derived-metric generation.
• Experience designing event-driven services and data-ingestion pipelines using Kafka, including integrations with SQL databases, analytical platforms, APIs, and observability systems.
• Strong experience with data modeling, dataset contracts, pre-aggregation, read models, caching, query optimization, and data-quality controls.
• Experience building secure, multi-tenant SaaS platforms with tenant isolation, authentication, authorization, and secure service-to-service communication.
• Experience working with AI/LLM platforms and production AI workloads, including model orchestration, RAG, evaluation, guardrails, or runtime observability.
• Good understanding of REST, OAuth, JSON, SQL, NoSQL databases, and Python or Bash scripting.
• Experience with CI/CD, automated testing, production monitoring, incident response, and Agile development practices.
• Experience with Azure, AWS, Google Cloud, and open-source technologies.
• Ability to lead multi-quarter roadmaps, make practical build-versus-reuse decisions, and align engineering, product, UX, security, platform, and observability teams. 

Extra Awesome

• Experience with OpenTelemetry, VictoriaMetrics, Prometheus/MetricsQL, Grafana Loki/LogQL, Grafana Tempo/TraceQL, Alertmanager, or Open Policy Agent.
• Experience integrating with Databricks, Delta Lake, Power BI, or other analytical data platforms.
• Experience building configurable dashboard systems, data visualization frameworks, or design-system-based frontend platforms.
• Experience with AI governance, model risk management, compliance, GRC, audit evidence, or regulatory reporting.
• Experience with graph data models, dependency maps, entity resolution, or supply-chain analysis.
• Experience designing SDK telemetry, model gateways, runtime instrumentation, or post-market monitoring.
• Proficiency in Kubernetes, including cluster deployment, scaling, and management is highly desirable.
• Background in enterprise, regulated, or security-focused environments. 

For California, Colorado, Connecticut, Nevada, New York, Rhode Island, and Washington-based candidates: the annual base pay range for this role is listed below. Within this range, individual pay is determined by several factors, including location, job-related skills, work experience, and relevant education and/or training. This role may also be eligible for discretionary bonuses, equity, and/or commissions, as well as benefits.