The Challenge
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.
Your Mission
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.
You Are
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.