[Hiring] Senior Staff Privacy Engineer @ServiceNow

Role Description

Our AI products rely on sensitive data to enable customers to get work done. With this in mind, privacy is a crucial part of ensuring that data is handled properly throughout the workflow, from what we collect and how we use it to the controls we apply across models, tools, logs and data pipelines. In this role, you will be a key privacy engineer, writing code and shaping the architecture and protections across our products. You will improve sensitive data detection and masking, assess the privacy risks of ML models, and own the implementation of customer data-use and retention controls. You will work with our Privacy, ML, Security, Product and Infrastructure teams from design through production.

This is a Senior Staff individual contributor role. You will be hands on, setting technical direction across teams and writing production code.

What you get to do in this role:

• Assess, benchmark and select ML models and techniques that meet our privacy requirements.
• Build representative evaluation datasets and compare detection coverage, false positives, latency, cost and the impact on product quality.
• Own the implementation of those models in our products, from prototype through production.
• Train or fine-tune where needed, build the surrounding services and APIs, and optimize inference performance and reliability.
• Build and deploy sensitive data detection, masking, redaction and tokenization for structured and unstructured data across logs, traces, APIs, analytics and annotation tools.
• Implement consistent controls for when data is masked and who can access the unmasked content.
• Build privacy evaluations for ML models and the systems around them, including memorization, training-data extraction, membership inference and sensitive data disclosure through retrieval or tool use.
• Implement mitigations and add regression tests to model and product release workflows.
• Write and maintain code that enforces customer requirements for data use, access, retention and deletion across services and data stores.
• Prototype and implement privacy-preserving approaches to evaluation and synthetic data.
• Measure privacy risk and utility, validate the assumptions behind the approach, and integrate suitable solutions into our ML pipelines.
• Conduct privacy design reviews with engineering, identify gaps in proposed data flows and architectures, and own or partner on the code changes needed to address them.
• Build reusable components and engineering standards that help teams apply these protections consistently.
• Monitor privacy controls and models in production, investigate failures, and ship improvements.
• Use error analysis and production feedback to improve detection quality, address regressions and close customer-reported privacy issues.

What success looks like in your first year:

• ML models selected and deployed for priority privacy use cases, with measured improvements in detection quality and acceptable production latency and cost.
• Shared masking and data protection components integrated into the highest-priority product surfaces, with automated tests for coverage and access behavior.
• Repeatable privacy evaluations running as part of model and product releases, with findings translated into shipped fixes.
• Priority data-use, retention and deletion requirements implemented and verified in production, with monitoring that identifies failures.

Qualifications

• Typically 7+ or more years building production software, including substantial experience in privacy engineering and applied ML.
• Strong Python skills and experience with Go, Java, C++ or another production systems language.
• Hands-on experience evaluating, selecting and deploying ML models, including dataset curation, model adaptation or fine-tuning, error analysis and model serving.
• Experience building sensitive data detection and masking systems, including their accuracy, performance and integration tradeoffs.
• Experience assessing privacy risks in ML and LLM systems and implementing mitigations.
• Deep understanding of data minimization, pseudonymization, anonymization and re-identification risk.
• Experience building data protection and lifecycle controls in distributed cloud systems.
• A record of taking ambiguous engineering problems from design through delivery, setting technical direction across teams and mentoring engineers.

Requirements

• Preferred experience applying differential privacy or other privacy-enhancing technologies.
• Privacy engineering for agentic systems, retrieval-augmented generation, embeddings or synthetic datasets.
• Experience in enterprise, multi-tenant or regulated environments, and translating privacy requirements such as GDPR and CCPA into technical controls.

Company Description

Moveworks is the Agentic AI Assistant platform that empowers the entire workforce. Our platform enables employees to converse with all of their business systems through natural language to quickly find answers and automate tasks. Powered by the world's most advanced LLMs, our proprietary models, and a sophisticated Agentic AI platform, we're transforming how work gets done by allowing AI to take initiative, streamline complex workflows, and continuously learn and adapt.

Moveworks is trusted by over 5.5 million employees at more than 350 of the world’s largest companies, including 10% of the Fortune 500, to automate everyday tasks and streamline business operations.

Recognized on the Forbes Cloud 100 and AI 50 lists, Moveworks was also named one of Fast Company’s 2025 Most Innovative Companies and Inc’s Best in Business, in the Best in Innovation category.

Moveworks was also recognized at Microsoft’s 2025 Partner of the Year and in 2024, received the AI Breakthrough Award.

In December 2025, Moveworks was acquired by ServiceNow, marking a pivotal milestone in our journey to create a single front door to work for all business systems.

By joining our team, you’ll be at the forefront of the AI transformation, backed by the global scale of ServiceNow and the agility of a high-growth company.