Lead Data Privacy Engineer in United States

About the Team The Privacy Engineering Team at OpenAI is committed to integrating privacy as a foundational element in OpenAI's mission of advancing Artificial General Intelligence (AGI). Our focus is on all OpenAI products and systems handling user data, striving to uphold the highest standards of data privacy and security. We build essential production services, develop novel privacy-preserving techniques, and equip cross-functional engineering and research partners with the necessary tools to ensure responsible data use. Our approach to prioritizing responsible data use is integral to OpenAI's mission of safely introducing AGI that offers widespread benefits. About the Role As a part of the Privacy Engineering Team, you will work on the frontlines of safeguarding user data while ensuring the usability and efficiency of our AI systems. You will help us understand and implement the latest research in privacy-enhancing technologies such as differential privacy, federated learning, and data memorization. Moreover, you will focus on investigating the interaction between privacy and machine learning, developing innovative techniques to improve data anonymization, and preventing model inversion and membership inference attacks. This position is located in San Francisco. Relocation assistance is available. In this role, you will: Design and prototype privacy-preserving machine-learning algorithms (e.g., differential privacy, secure aggregation, federated learning) that can be deployed at OpenAI scale. Measure and strengthen model robustness against privacy attacks such as membership inference, model inversion, and data memorization leaks—balancing utility with provable guarantees. Develop internal libraries, evaluation suites, and documentation that make cutting-edge privacy techniques accessible to engineering and research teams. Lead deep-dive investigations into the privacy–performance trade-offs of large models, publishing insights that inform model-training and prod

Principal Data Privacy Architect Description - Job Summary - Role Purpose • Lead and oversee complex, cross-functional privacy and data protection programs from strategy through implementation, ensuring alignment across business, technical, legal, and compliance stakeholders. • This role will design and implement scalable, AI-ready data privacy architecture across enterprise data environments, applications, and AI-enabled workflows. • The Principal Data Privacy Architect will serve as a hands-on subject matter expert responsible for embedding privacy-by-design, consent enforcement, data sovereignty, data loss prevention, and compliance controls into large, complex global data environments. • The architect will partner closely with Data Engineering, Cybersecurity, Legal, Privacy, AI Governance, Product, and Enterprise Architecture teams to ensure customer, employee, partner, and sensitive enterprise data is accessed, processed, shared, retained, and protected in a compliant, secure, and trustworthy manner. - Why This Role Matters • Architect for Trust & Scale: Build reusable privacy architecture patterns that enable secure, compliant, and scalable data usage across platforms, products, and regions. • Enable Responsible AI: Design privacy guardrails for AI agents, generative AI, RAG pipelines, model inputs and outputs, embeddings, vector stores, and automated data workflows. • Reduce Risk While Enabling Innovation: Translate privacy, consent, regulatory, and data sovereignty obligations into practical engineering controls that accelerate business outcomes. Responsibilities - Think Customer First • Embed customer trust, transparency, and privacy-by-design principles into enterprise data platforms and customer-facing applications. • Design consent-aware data access and usage p

Overview: The Data Acquisition team within the Foundations organization at OpenAI is responsible for all aspects of data collection to support our model training operations. Our team manages web crawling and GPTBot services and works closely with Data Processing, Architecture, and Scaling teams. We are looking for a skilled Software Engineer to join our Data Acquisition team. Responsibilities: Own and lead engineering projects in the area of data acquisition including web crawling, data ingestion, and search. Collaborate with other sub-teams, such as Data Processing, Architecture, and Scaling, to ensure smooth data flow and system operability. Work closely with the legal team to handle any compliance or data privacy-related matters. Develop and deploy highly scalable distributed systems capable of handling petabytes of data. Architect and implement algorithms for data indexing and search capabilities. Build and maintain backend services for data storage, including work with key-value databases and synchronization. Deploy solutions in a Kubernetes Infrastructure-as-Code environment and perform routine system checks. Conduct and analyze experiments on data to provide insights into system performance. Qualifications: BS/MS/PhD in Computer Science or a related field. 4+ years of industry experience in software development. Experience with large web crawlers a plus Strong expertise in large stateful distributed systems and data processing. Proficiency in Kubernetes, and Infrastructure-as-Code concepts. Willingness and enthusiasm for trying new approaches and technologies. Ability to handle multiple tasks and adapt to changing priorities. Strong communication skills, both written and verbal. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an

About the Team The Privacy Engineering team builds the systems and technical foundations that govern how user data is understood, retained, accessed, and used across OpenAI. We partner with Product, Data, Infrastructure, Security, and Legal to translate policy and trust commitments into durable architecture and enforceable controls. Our work spans data inventory and mapping, classification and lineage, retention and deletion, access governance, purpose and usage controls, auditability, and lifecycle automation. We aim to make policy-aligned data handling the default while giving teams clear, reliable primitives for building and operating products at scale. About the Role We are looking for an experienced Software Engineer to drive the architecture and execution of user data governance across OpenAI. You will define technical direction, build shared platforms and controls, and lead cross-functional programs that make data flows discoverable, policies enforceable, and ownership explicit. This role is well suited to a senior engineer who can move between deep systems design and organization-wide influence, turn ambiguous requirements into pragmatic roadmaps, and operate high-trust systems end to end. This position is based in San Francisco. Relocation assistance is available. In this role, you will: Set the technical strategy and architecture for user data governance across data mapping, classification, lineage, retention, deletion, access, and permitted usage. Design and build shared services, APIs, metadata systems, and policy-enforcement mechanisms that make governance controls consistent, scalable, and auditable. Establish reliable inventories of user data, system ownership, data flows, and policy applicability across products, infrastructure, analytics, and research systems. Partner with Product, Data, Infrastructure, Security, and Legal leaders to define decision rights, translate requirements into controls, and drive adoption across teams. Own governance systems

A Career with Point72’s Technology Team As Point72 reimagines the future of investing, our Technology team is constantly evolving our firm’s IT infrastructure and engineering capabilities, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts who experiment and work to discover new ways to harness open-source solutions, modern cloud architectures, and sophisticated Artificial Intelligence (AI) solutions, while embracing enterprise agile methodologies. Our commitment to building and innovating in the AI space provides the framework intended to drive smarter decision making and enhance how we build and operate our platforms and applications. As a member of Point72’s Technology team, we encourage and support your professional development from day one—helping you advance your technical skills, contribute innovative ideas, and satisfy your own intellectual curiosity—all while delivering real business impact for our multi-billion-dollar global business. What you’ll do Develop and maintain the information security policy and standards library, aligning it with business priorities, regulatory expectations, and control objectives Lead independent assessments of the information security program, including regulatory examinations and third-party evaluations Identify technology risks across a complex business environment and drive mitigation aligned with our firm’s standards and control expectations Investigate data privacy inquiries and privacy-related events, assess business impact, and coordinate timely response activities Partner with technology, legal, compliance, and business stakeholders to translate risk findings into practical remediation plans Advise control owners on policy interpretation, risk treatment, and evidence expectations for assessments and examinations Prepare clear reports for management on team activity, emerging risks, remediation progress, and key decisions Maintain accurate risk, policy, priv

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. We're seeking an experienced Commercial Counsel to join our growing legal team and serve as a strategic partner to our rapidly expanding enterprise sales organization. In this high-impact role, you'll drive complex commercial negotiations that fuel our growth, working closely with our sales teams to close sophisticated technology agreements with enterprise customers across diverse industries. You'll play a critical role in scaling our commercial legal processes while navigating the evolving landscape of AI-powered development tools and ensuring our customers can confidently deploy Replit's platform in their organizations. What You'll Do Drive Enterprise Deals : Serve as the lead legal advisor for complex, high-value enterprise sales transactions, working directly with our Account Executives and customer legal teams to negotiate and close sophisticated software agreements Navigate AI & Technology Compliance : Help enterprise customers understand and navigate the legal and regulatory implications of adopting AI-powered development tools, addressing data privacy, security, and compliance requirements across various industries Build Scalable Frameworks : Design and implement contract playbooks, template agreements, and streamlined processes that enable our sales team to move quickly while maintaining legal rigor as we scale Risk Management : Identify, analyze, and proactively manage complex commercial and legal risks while maintaining deal velocity in our fast-paced, high-growth environment Cross-Functional Partnership : Collaborate closely with Product, Engineering, Security, and Privacy teams to ensure our commercial offerings align with product capabilities and regulatory requirements Strategic Advisory : Provide st

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. Role Summary: This role will lead the data engineering function supporting People Analytics, including AI-assisted workforce analytics on Snowflake. This is a player-coach role requiring hands-on technical leadership plus people leadership, with strong business partnership and the ability to balance speed, quality, governance, and innovation. What you’ll do: Manage and develop data engineers Manage, coach, and grow a team of data engineers. Set expectations for quality, collaboration, delivery, and technical ownership. Create a strong engineering culture where people solve hard problems, move quickly, and enjoy the work. Collaborate with cross-functional teams, such as other data engineers, people analysts, data scientists, and business stakeholders, to translate requirements into production-ready deliverables, and communicate technical trade-offs to non-technical partners. Stay hands on Write and review production code. Lead design reviews, code reviews, and technical problem solving. Step into critical pipelines, models, or AI workflows when needed. Build scalable People data foundations Design and maintain sustainable data models, pipelines, semantic layers, and testing frameworks. Establish team practices for documentation, lineage, data quality, and observability. Own engineering standards Set standard

About the Team The Applied team brings OpenAI’s technology to the world through products used by hundreds of millions of people and by developers and businesses building on our APIs. We work across research, engineering, product, policy, safety, and operations to deploy frontier AI systems responsibly and safely. The Trust & Safety Data Engineering team builds the data foundations that help OpenAI understand, detect, investigate, and mitigate abuse and safety risks across our products. We partner with Integrity, Investigations, Safety Systems, Product Policy, Privacy, Data Science, Engineering, and Data Platform to create reliable, privacy-safe datasets and pipelines for fraud and abuse detection, enforcement workflows, safety measurement, ML feature generation, launch readiness, and transparency reporting. About the Role We are hiring a Technical Lead Manager to lead and grow the Trust & Safety Data Engineering team. This is a hands-on leadership role for someone who can set strategy, shape data architecture, align senior stakeholders, coach engineers, and drive execution on high-impact data systems. You will help turn fragmented launch and incident support into durable, reusable, privacy-safe data foundations that Trust & Safety teams can rely on. The systems your team builds will help OpenAI detect risk, investigate abuse, power operational workflows, develop and evaluate safety models, measure interventions, support product launches, and report accurately on platform integrity. In This Role, You Will Lead and grow a high-performing Trust & Safety Data Engineering team. Define the roadmap and technical strategy for Trust & Safety data systems. Build canonical, privacy-safe datasets and pipelines for abuse detection, fraud detection, risk signals, enforcement, scaled review, transparency reporting, and safety monitoring. Create reusable foundations for Trust & Safety model development, including features, labels, training data, backtesting,

Privacy Program Manager Description - Privacy Program Manager - Products & Services Privacy Job Summary This role is responsible for providing strategic privacy advisory, guidance and program management support to HP's Products & Services organizations to ensure compliance with global privacy, data protection, AI governance, and regulatory requirements. The role partners closely with product, engineering, legal, security, data governance, and business teams to embed privacy-by-design principles throughout the product lifecycle, assess privacy risks, and drive implementation of compliant solutions that enable innovation while protecting customer, employee, and partner data. The role leads privacy initiatives, manages complex cross-functional programs, develops governance processes, and serves as a trusted advisor to stakeholders on privacy requirements impacting products, services, digital platforms, AI/ML solutions, and emerging technologies. Success in this role requires strong program management, risk assessment, stakeholder engagement, and regulatory interpretation skills. Responsibilities Manage and lead privacy programs supporting HP Products & Services teams to ensure compliance with global privacy and data protection regulations, including GDPR, CCPA/CPRA, LGPD, PIPL, and other applicable international requirements. Serve as a trusted privacy advisor for product, service, software, AI/ML, cloud, and digital platform initiatives by providing practical guidance throughout the development lifecycle. Conduct and facilitate Privacy Impact Assessments (PIAs), Data Protection Impact Assessments (DPIAs), AI risk assessments, and related reviews to identify and mitigate privacy risks. Partner with business, engineering, legal, cybersecurity, data governance, and compliance stakeholders to in

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: The Data Stewardship team is a group of passionate data practitioners with a diverse background in analytics, data modeling, governance, compliance, and scaled data quality. We are responsible for ensuring Airbnb is meeting its compliance obligations across our data ecosystem and ensuring data consumers are able to easily identify the best data for their needs. We support the pipelines, programs, and policy-bodies that make this possible. You’ll be part of the overall Data Infrastructure organization that is responsible for online and offline data infrastructure across the company, and the components that transition data between these environments. The Difference You Will Make Set the North Star: you will define the multi-year vision for Data Governance and Data Quality that scales with our global business and evolving AI landscape. Organizational Influence: Act as a primary consultant for executive leadership on data governance, ensuring that compliance and stewardship are integrated into the data product lifecycle from day one. A Typical Day Architect Ecosystems: Lead the design of overarching data architectures that don't just solve today’s batch needs but anticipate future real-time and AI-driven requirements. Scale Best Practices: Rather than just "ensuring quality," you will define the best practices, tooling, and culture that enable data organizations to maintain high-quality data autonomously. Policy Stewardship: Lead cross-functional task forces (Infosec, Legal, Privacy) to navigate complex regulatory landscapes (like GDPR or AI Act) and translate them int

About the Team The Applied organization brings OpenAI’s most advanced technology to the world through products like ChatGPT and the APIs that power a growing ecosystem of developer and enterprise applications. Data Engineering builds and operates the trustworthy, secure, and reliable data systems that power decisions across OpenAI. About the Role We’re looking for a Data Engineering Manager to lead the Growth & Revenue data engineering team. This leader will own the data strategy and execution for the data subject areas spanning growth accounting across all product surfaces, product partnerships, checkout, billing, payments, revenue, and monetization, helping OpenAI understand how people adopt, engage with, and pay for our products. You will partner closely with several Data Science, Business, and Engineering partners to connect product behavior to trustworthy subscriber, payment, and revenue measurement. In this role, you will: Build, manage, and grow a high-performing, inclusive team across the Growth & Revenue data subject areas. Define the data strategy for all the data subject areas you own. Deliver durable, well-modeled data products that connect product behavior, subscription state, checkout events, payment outcomes, and revenue. Establish trusted metric definitions and data quality standards so product, growth, finance, and executive leaders can make fast, consistent decisions. Partner with Data Science and Product teams to support experimentation, causal measurement, funnel analysis, and scalable self-serve analytics. Partner with Finance and Financial Engineering to ensure analytical revenue views reconcile to financial truth and production billing systems. Raise operational excellence for critical pipelines, including reliability, observability, privacy, governance, and incident response. Set a clear roadmap, make principled tradeoffs, and communicate progress and risk across technical and business stakeholders. You might thrive in this role if yo

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. The Data Governance team makes sure Plaid handles consumer and customer data responsibly — and can prove it. Our mission is to enforce Plaid's privacy commitments and regulatory obligations in the systems themselves rather than in policy documents: we build the platform and controls that govern how data flows through Plaid — where it lives, who can use it, for what purpose, and for how long. That includes verifiable deletion of consumer data on request, enforcement of data-use restrictions so downstream systems can only use data in permitted ways, and the cataloging and classification that let Plaid know what data it holds and how sensitive it is. We operate at the scale of Plaid's entire data footprint, and correctness and auditability matter to us as much as throughput. As a Staff Software Engineer on Data Governance, you will set the technical direction for how Plaid enforces data governance at scale. You'll lead the design of distributed backend systems that reliably delete, restrict, and track data across dozens of services, making architectural decisions whose blast radius spans the whole company. You'll drive multi-quarter initiatives from ambiguous privacy and regulatory requirements through

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . About tvScientific tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying, optimization, measurement, and attribution in one, efficient platform. Our platform is built by industry leaders with a long history in programmatic advertising, digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business. We are seeking a Staff Data Engineer to lead the design, implementation, and evolution of our identity services and data governance platform. This role is critical to ensuring trusted, privacy-safe, and well-governed data across the organization. You will work at the intersection of da

What you’ll do Act as the technical lead for large parts of the scanner platform: system architecture, codebase structure, and long-term maintainability. Own core runtime foundations: distributed control, state management, fault handling, and reliability. Drive engineering rigor: testability, code quality, review standards, performance regression prevention, and release processes. Build robust observability: logs, metrics, traces, and replayable diagnostics (with privacy constraints). Collaborate with hardware and recon/ML teams to define interfaces, data contracts, timing/synchronization, and failure modes. Lead complex refactors (e.g., message passing / RPC boundaries, modularization, concurrency model) without halting forward progress. What we’re looking for Deep software architecture experience for real-world systems: robotics, instrumentation, medical devices, or other complex distributed products. Strong Python and concurrency background (asyncio, multiprocessing, profiling, performance engineering). Track record of shipping systems that are observable, debuggable, and resilient. Strong technical leadership: clarity, pragmatic trade-offs, and mentoring. Useful experience Building but rock-solid systems: clear interfaces (gRPC/protobuf or equivalent), strong state modeling, and failure handling. High-leverage engineering habits on a lean team: good tests, CI, reproducible dev environments, and fast code review. Practical performance + concurrency work in Python (asyncio, profiling, multiprocessing) and comfort debugging distributed behavior. Security-minded device software: safe defaults, encrypted data paths, and disciplined handling of PII/PHI. Operational thinking: remote updates/management, excellent logging, and diagnostics that make real hardware debuggable.

About the Team OpenAI’s Governance, Risk, and Compliance team helps ensure security and privacy are grounded in how our products and systems actually operate. Assurance Operations partners with Security, Engineering, Infrastructure, Product, Privacy, and Legal to make controls provable, risk decisions explicit, and audit readiness a result of well-designed systems. About the Role We are hiring a technical, product-minded GRC builder who can own consequential audits while improving the control and evidence systems behind them. You will build a reusable common control framework, use Codex to automate assurance work, validate changing system scope, and turn repeated audit friction into measurable improvements. We are looking for someone who questions inherited assumptions, solves novel problems creatively, works closely with engineers, and makes the next audit easier by improving the underlying system. You’ll be responsible for: Lead external, internal, customer, and certification audit work from scoping through evidence review, fieldwork, remediation, and closeout. Build a common control framework linking risk, control intent, implementation, owner, system, environment, evidence, and applicable frameworks. Validate actual scope and ownership instead of assuming last year's controls, product boundaries, or evidence remain accurate. Use Codex to build and test evidence checks, control mappings, request triage, owner workflows, monitoring, and remediation reporting. Partner with engineers on cloud architecture, identity, logging, data flows, software changes, vulnerabilities, and control effectiveness. Design maintainable, permission-aware tools that preserve source provenance, human review, and evidence integrity. Reduce repeated requests and operational burden for control owners through measurable workflow improvements. Define roadmaps, decision rights, milestones, success metrics, and clear cross-functional escalations. We’re looking for someone with: Direct ownership