About the job
Empowering Trust through Innovation
At OneTrust, we are committed to fostering innovation through the ethical utilization of data and artificial intelligence. We believe that trust in data should enhance, not hinder, productivity. This vision led to the inception of the first technology platform dedicated to responsible data usage in 2016. As AI continues to revolutionize the data landscape, OneTrust is at the forefront, redefining the standards of responsible innovation. Our AI-Ready Governance Platform™ integrates regulatory intelligence, automation, and cohesive governance workflows, empowering businesses to harness the potential of AI while ensuring robust governance to mitigate data misuse on a large scale. Trusted by thousands globally, OneTrust is shaping a future where reliable data is a transformative asset for both business and society.
Your Challenge
We are in search of a Principal Domain Architect to articulate and propel the technical vision for AI-native and agentic systems within our platform. This pivotal role merges profound system architecture expertise with AI-driven innovation and strategic technology leadership to develop scalable, robust, and enterprise-level solutions. The Principal Architect will collaborate closely with Product, AI Platform teams, the Architecture Guild, and engineering leadership to steer the design of intricate distributed systems, impact the product roadmap, and champion the adoption of contemporary AI-native architectures throughout the organization. This leader will also identify emerging engineering advancements, translating them into strategic business opportunities while enhancing engineering efficiency and technical excellence across our product suite.
Your Mission
- Define and deliver architecture for AI-native agentic systems, enabling scalable and enterprise-grade multi-agent solutions.
- Create and assess failure mode scenarios for agentic workflows and integrate architectural safeguards to ensure resilience and reliability.
- Provide deep expertise in LLM architectures, prompt engineering, RAG approaches, model selection, model training, LoRA knowledge, cost optimization, performance, security, and quality considerations.
- Drive technology transformation initiatives that align with business objectives and foster innovation.

