Principal Domain Architect

OneTrust•San Francisco, CA

2d•Hybrid

About The Position

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. The Challenge We are seeking a Principal Domain Architect who will define and drive the technical vision for AI-native and agentic systems across the platform. This role combines deep system architecture expertise, AI innovation, and strategic technology leadership to build scalable, reliable, and enterprise-grade solutions. The Principal Architect will work closely with Product, AI Platform teams, Architecture Guild, and engineering leadership to guide the design of complex distributed systems, influence the product roadmap, and drive the adoption of modern AI-native architectures across the organization. This leader is expected to identify emerging engineering advancements and translate them into strategic business opportunities, while improving engineering efficiency and technical excellence across products.

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
16+ years of software engineering experience with deep expertise in distributed systems.
Extensive experience with Java-based development using REST APIs, Spring Boot, and microservices architectures.
Strong experience designing distributed, asynchronous, and event-driven architectures.
Expertise building low-latency, high-throughput data pipelines and large-scale data platforms.
Experience with data streaming and event processing technologies such as Kafka, Kinesis, Spark, or Flink.
Strong knowledge of data structures, algorithms, distributed algorithms, and system programming.
Experience with fault-tolerant messaging systems such as Kafka, RabbitMQ, AMQ, or ZeroMQ.
Experience working with distributed data stores including MongoDB, Cassandra, CockroachDB, or CouchDB.
Experience integrating applications with search platforms such as Elasticsearch or Solr.
Proven experience mentoring engineers and building strong engineering practices.
Strong ability to create and maintain architecture documentation and system design artifacts.
Excellent leadership, verbal, and written communication skills.

Nice To Haves

Master’s degree in Computer Science, Engineering, or related field.
Experience running large-scale web services and distributed platforms.
Deep understanding of system performance tradeoffs, load balancing, and high-availability architectures.
Experience with cloud-native and serverless architectures.
Experience designing graph-based data models and graph architectures.
Experience building AI-native platforms or LLM-powered systems.

Responsibilities

Define and deliver architecture for AI-native agentic systems, enabling scalable and enterprise-grade multi-agent solutions.
Create and evaluate failure mode scenarios for agentic workflows and incorporate 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 within the domain, enabling teams to adopt modern AI-native architectures and engineering practices.
Stay current with rapid advancements in the agentic AI ecosystem, continuously evaluating emerging frameworks, tools, and architectural patterns.
Champion technical exploration and spikes to test new ideas, validate feasibility, and guide long-term architectural decisions.
Collaborate closely with the AI Platform team to influence platform capabilities and ensure alignment with enterprise architecture.
Define metrics, evaluation frameworks, and observability standards for agentic systems.
Provide architectural guidance and oversight to engineering squads, reviewing designs and co-creating solutions for complex initiatives.
Act as a technology leader for the domain, influencing the Architecture Guild and driving best practices across engineering teams.
Ensure teams adopt architecture governance standards and best practices.
Champion technical controls and disciplined engineering practices to proactively manage architectural complexity and technical debt.
Design and build high-performance distributed systems capable of supporting enterprise workloads.
Recognize industry trends and proactively influence the product and engineering roadmap.
Mentor engineers and architects, strengthening the organization’s technical leadership and architectural maturity.
Design large-scale distributed systems and AI-powered architectures that support multiple products and integrations.
Create and maintain architecture models, system diagrams, and technical design documentation covering current and future state architecture.
Conceive and evolve product and service architectures ensuring scalability, reliability, and operational efficiency.
Ensure systems are designed for high availability, performance, and ease of operations.
Contribute to company-level engineering strategy and evaluate the business impact of emerging technologies.
Lead engineering initiatives to improve platform capabilities and engineering productivity.
Participate in strategic programs that impact company-wide technical direction.
Influence cross-organizational architecture decisions and collaborate with Director and VP level stakeholders.
Recommend technologies and frameworks that increase engineering productivity and system reliability.
Oversee technical aspects of major initiatives and ensure high engineering standards.
Mentor engineers and technical leaders to strengthen system design capabilities and engineering best practices.