Engineering Jobs

We’re looking for an Engineering Manager to lead our Sensitive Data Scanner (SDS) Telemetry team. The SDS group’s mission is to be the world’s easiest-to-use tool to discover, classify, manage, and report sensitive data risks across cloud, on-premise, and code environments. This team builds and scales the detection capabilities that scan all telemetry data flowing into Datadog — logs, APM spans, and RUM events — operating in streaming, at processing time, and at very large scale. You’ll lead a small, close-knit team based in Paris, with the opportunity to shape how the team grows as SDS Telemetry’s scope expands. It’s a chance to combine hands-on technical leadership with direct customer and product impact in the security and observability space. At Datadog, we place value in our office culture — the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Lead and grow a team of engineers building real-time sensitive data detection across Datadog’s Logs, APM, and RUM telemetry pipelines Partner closely with the Logs, APM, and RUM teams, plus Datadog’s Trust & Safety team, to align on roadmap and integration priorities Shape product direction by working closely with Product, grounding decisions in customer needs and business impact Stay hands-on: contribute to design decisions and participate in the team’s on-call rotation Recruit, mentor, and develop engineers as the team grows beyond its initial size Help build a strong engineering culture as part of Datadog’s broader Sensitive Data Scanner group Who You Are: You have experience building and shipping revenue-generating products, with strong product acumen and a customer-first mindset You have hands-on experience with Go and/or Java, and a track record building distributed, streaming systems at scale You have experience managing engineers — or are

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . As a Group Product Manager on the Financial Engineering team within Platform , you'll define how Coinbase's finance infrastructure scales to support hundreds of billions of dollars in annual transaction volume. This team empowers every finance function at Coinbase to operate with precision, agility, and foresight, and you'll own the product strategy for finance transformation, automation, and AI-driven tooling. This is a high-visibility role with direct exposure to Coinbase's Chief Accounting Officer, and you'll lead a team of PMs to deliver mission-critical systems across accounting, treasury, and financial reporting. What you'll do: Own the product strategy and roadmap for finance transformation, including process automation, AI-driven insights, and system modernization, ensuring alignment with Finance leadership priorities and company-wide objectives. Lead and develop a team of product managers, setting the bar for product craft, stakeholder management, and technical depth across the Financial Engineering organization. Drive cross-functional execution of high-impact initiatives spanning reconciliation tooling, SOX-compliant change management for the financial reporting pipeline, new product finance onboarding, and self-serve tools for Accounting and Treasury. Partner directly with senior leaders in Finance, Product, and Engineering to prioritize a portfolio of ini

OMT Planning Site Inventory Control (SIC) Engineer-Engineering-Taiwan — Taoyuan - Fab 11, Taiwan. Apply via Workday.

Intern 2027 - DRAM Customer Enablement Engineering — Taichung - Fab 16, Taiwan. Apply via Workday.

Staff/ Principa/ MTS Agentic AI Architect – Knowledge Engineering — Hyderabad - Phoenix Aquila, India. Apply via Workday.

About the Team The Privacy Engineering team builds secure, reliable systems that help OpenAI meet its legal obligations while protecting user data. We partner closely with Legal and engineering teams across OpenAI to support lawful data access requests and other critical legal workflows. Our work turns complex, high-stakes processes into auditable and dependable technical systems with clear human oversight and strong privacy and security controls. About the Role We’re looking for a full-stack Software Engineer to build the internal tools and data pipelines that power lawful data access request workflows and Legal Operations. You will work across product and data systems to make authorized retrieval and case handling accurate, efficient, and auditable. This role is well suited to someone who enjoys translating ambiguous operational requirements into durable systems, cares deeply about sensitive-data handling, and wants to improve both technical reliability and the day-to-day experience of the people operating these workflows. In this role, you will: Design, build, and operate backend systems and workflow tooling for the full lifecycle of lawful data access requests, from intake and scoping through authorized retrieval, review, preparation, and audit. Build reliable data pipelines and interfaces across products and data stores so authorized teams can locate and handle the right records accurately and reproducibly. Implement least-privilege access, approval gates, provenance, audit trails, data minimization, and safe failure modes for sensitive workflows. Partner with Legal and Legal Operations to translate legal and operational requirements into clear technical designs and intuitive operator experiences. Identify responsible automation opportunities that reduce repetitive work while preserving human review, judgment, and accountability. Own production systems through testing, observability, incident response, documentation, and continuous reliability improvements. Hel

About the Team The Privacy Engineering team builds secure, reliable systems that help OpenAI meet its legal obligations while protecting user data. We partner closely with Legal and engineering teams across OpenAI to support lawful data access requests and other critical legal workflows. Our work turns complex, high-stakes processes into auditable and dependable technical systems with clear human oversight and strong privacy and security controls. About the Role We’re looking for a full-stack Software Engineer to build the internal tools and data pipelines that power lawful data access request workflows and Legal Operations. You will work across product and data systems to make authorized retrieval and case handling accurate, efficient, and auditable. This role is well suited to someone who enjoys translating ambiguous operational requirements into durable systems, cares deeply about sensitive-data handling, and wants to improve both technical reliability and the day-to-day experience of the people operating these workflows. In this role, you will: Design, build, and operate backend systems and workflow tooling for the full lifecycle of lawful data access requests, from intake and scoping through authorized retrieval, review, preparation, and audit. Build reliable data pipelines and interfaces across products and data stores so authorized teams can locate and handle the right records accurately and reproducibly. Implement least-privilege access, approval gates, provenance, audit trails, data minimization, and safe failure modes for sensitive workflows. Partner with Legal and Legal Operations to translate legal and operational requirements into clear technical designs and intuitive operator experiences. Identify responsible automation opportunities that reduce repetitive work while preserving human review, judgment, and accountability. Own production systems through testing, observability, incident response, documentation, and continuous reliability improvements. Hel

About the Team The Privacy Engineering team builds secure, reliable systems that help OpenAI meet its legal obligations while protecting user data. We partner closely with Legal and Engineering teams across OpenAI to support lawful data access requests and other critical legal workflows. Our work turns complex, high-stakes processes into auditable and dependable technical systems with clear human oversight and strong privacy and security controls. About the Role We’re looking for a full-stack Software Engineer to build the internal tools and data pipelines that power lawful data access request workflows and Legal Operations. You will work across product and data systems to make authorized retrieval and case handling accurate, efficient, and auditable. This role is well suited to someone who enjoys translating ambiguous operational requirements into durable systems, cares deeply about sensitive-data handling, and wants to improve both technical reliability and the day-to-day experience of the people operating these workflows. This role is based in San Francisco, CA, with two additional locations under consideration: London, UK, and Dublin, Ireland. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, build, and operate backend systems and workflow tooling for the full lifecycle of lawful data access requests, from intake and scoping through authorized retrieval, review, preparation, and audit. Build reliable data pipelines and interfaces across products and data stores so authorized teams can locate and handle the right records accurately and reproducibly. Implement least-privilege access, approval gates, provenance, audit trails, data minimization, and safe failure modes for sensitive workflows. Partner with Legal and Legal Operations to translate legal and operational requirements into clear technical designs and intuitive operator experiences. Identify responsible automation o

About the Team The Solutions Engineering team consists of trusted technical advisors who help organizations adopt OpenAI’s technology safely, effectively, and responsibly. We partner closely with customers, Sales, Product, Engineering, Research, and Security to translate frontier AI capabilities into practical workflows that create measurable impact. Cybersecurity is one of the most important areas where AI can help. As frontier models become increasingly capable of reasoning across code, logs, infrastructure, vulnerabilities, and security evidence, customers need expert guidance to evaluate and deploy these systems safely. Our Field Security Specialists help security leaders and practitioners apply OpenAI models, APIs, Codex, agentic workflows, and emerging cyber capabilities to real defensive challenges. About the Role We are looking for a Manager of Field Security Specialists to build and lead our customer-facing cyber solutions engineering function. This is a hands-on leadership role for someone who can develop an exceptional team while remaining close to the technology and our customers. You will establish the operating model for the function, raise the quality of specialist engagements, and personally support our most strategic and technically complex customer opportunities. You will work across CISO-level strategy, practitioner-level cybersecurity challenges, and hands-on solution design. Your team will help customers explore workflows including application security, secure software development, vulnerability management, threat modeling, cloud and identity security, SOC operations, detection engineering, incident response, and security validation. This is not an internal CISO or corporate incident-response role. It is a customer-facing leadership opportunity focused on helping defenders achieve safe, measurable outcomes with frontier AI. In this role, you will: Hire, coach, develop, and lead a high-performing team of Field Security Specialists. Establish the

About the Team The Applied AI Engineering team partners closely with customers to help them turn frontier AI capabilities into real products, workflows, and business impact. We act as trusted technical partners across strategy, solution design, architecture, implementation, evaluation, and adoption, working alongside customers to build and scale effective AI applications with OpenAI’s technologies. The Digital Natives segment serves technology and software companies that are building AI into the core of their products and businesses. These customers are often highly technical, move quickly, and are among the earliest adopters of OpenAI’s newest capabilities. Our Applied AI Engineers work directly with their engineering, product, and technical leadership teams to identify high-impact opportunities, solve complex technical challenges, and bring ambitious AI applications into production. About the Role We are seeking a Manager, Applied AI Engineering (Digital Natives) to lead the team responsible for the technical success of our most strategic technology and software customers in the Americas. In this role, you will lead a team of Applied AI Engineers who work hands-on with customers to design, build, evaluate, and scale AI applications. You will help determine where deep technical partnership can unlock the greatest customer and business impact, while developing repeatable approaches that allow the team to support a broad and fast-moving customer segment. As a manager, you will set the strategy and operating model for the team, coach and develop engineers, and serve as a senior technical partner to customers and internal stakeholders. You will work closely with Sales, Product, Engineering, and Research to connect what we learn from customers with OpenAI’s product direction and help customers take advantage of our newest capabilities. Success in this role will be measured by meaningful production applications, sustained adoption and usage, strong customer outcomes, and

About the Team The Core Network Engineering team owns the end-to-end networking stack that connects OpenAI’s compute infrastructure — spanning global WAN/edge connectivity, data-center networking, and high-performance host/xPU networking used for large-scale training and inference workloads. This team is responsible for ensuring networking is never the bottleneck to model training efficiency, cluster reliability, or fleet expansion. They design and operate the systems that provide predictable, high-throughput, low-latency connectivity across some of the world’s most advanced AI infrastructure. About the Role We’re looking for engineers to help build and operate the networking foundation behind OpenAI’s frontier AI systems. Depending on your background and area of focus, you may work across host networking, datacenter fabrics, or global WAN infrastructure. The problems span low-level systems software, distributed infrastructure, protocol readiness, observability, performance engineering, automation, and large-scale network operations. You’ll work on systems where microseconds of latency, tail performance, and network reliability directly impact model training efficiency and production serving performance. This role is ideal for engineers who enjoy operating close to the hardware/software boundary and solving performance-critical infrastructure problems at massive scale. In this role, you will: Design, build, and operate networking systems that support large-scale AI training and inference infrastructure Improve performance, reliability, and scalability across host networking, datacenter fabrics, and WAN systems Develop automation for provisioning, configuration management, validation, upgrades, and lifecycle management of networking infrastructure Build tooling and observability systems for network health, performance analysis, debugging, and automated remediation Optimize network performance across technologies such as RDMA, RoCE, InfiniBand, Ethernet, and high-perf

About the team The Applied AI Engineering (AAE) team is responsible for helping developers and enterprises turn the potential of generative AI into real-world impact. We act as trusted advisors and technical partners to customers and ecosystem partners, helping identify high-impact AI use cases and bring them into production through strong architectural guidance and hands-on execution. The Partner Applied AI Engineering organization works closely with strategic cloud providers, systems integrators, consultancies, and implementation partners to scale successful adoption of OpenAI technologies. As the leader of the AWS Partner AAE pod, you will manage a team of Applied AI Engineers focused on enabling AWS-aligned partners and their customers to build, deploy, and operationalize AI applications on OpenAI’s platform. About the role We are seeking a Manager, Partner Applied AI Engineering – AWS to lead a team of Applied AI Engineers supporting strategic AWS ecosystem partnerships. In this role, you will own the technical success strategy for AWS-aligned partners and help build scalable, repeatable ways for partners and their customers to adopt OpenAI technologies. Your team will guide partners and customers across the full AI implementation lifecycle—from identifying and shaping high-value use cases to solution design, architecture, production deployment, optimization, and adoption growth. You will work cross-functionally with internal and external stakeholders across Sales, Partnerships, Product, Research, and Engineering to ensure the voice of partners and customers informs our platform roadmap and how we bring OpenAI technology into production at scale. This role requires a blend of technical depth, customer leadership, operational rigor, and people management. Success will be measured through production deployments, partner technical maturity, API adoption growth, team development, and the overall impact of the AWS partner ecosystem. This role is based in our San Fra

About the Team OpenAI’s Financial Engineering (FinEng) team powers how revenue flows through our products—pricing & packaging, checkout, payments, subscriptions, and the financial infrastructure behind them. We partner with Product, Engineering, Risk, Finance, and Go-to-Market to make paying for OpenAI products seamless, reliable, and efficient worldwide. About the Role As a Data Scientist on FinEng, you’ll own the analytics and experimentation that improve our checkout and payments , subscriptions , and pricing & monetization systems. You’ll define the metrics that matter, build the source-of-truth data assets, and design experiments that increase conversion, reduce churn and payment failures, and expand global payment method coverage. Your work will directly influence revenue, customer experience, and how we scale internationally. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will Own checkout & payments analytics and experimentation across methods and locales (e.g., bank transfers, emerging rails), improving conversion while monitoring risk and latency. Build and run the experimentation program for in-house checkout—define success metrics and guardrails, execute staged rollouts, and use offline incrementality when online tests aren’t feasible. Create operational visibility and source-of-truth data with FinEng Data Engineering—land team-level metrics, SLAs, and self-serve dashboards that drive proactive action. Lead subscription, retention, and monetization analytics—ship launch-readiness for new subscription features, reduce involuntary churn (e.g., targeted retrials/nudges), and develop elasticity/FX frameworks toward pricing optimality. You might thrive in this role if you have 5+ years in a quantitative role (data science, product analytics, or experimentation) in high-growth or fintech environments Fluency in SQL and Python ,

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

About the Team The Applied AI Engineering team partners closely with customers to help them turn frontier AI capabilities into real products, workflows, and business impact. We act as trusted technical partners across strategy, solution design, architecture, implementation, evaluation, and adoption, working alongside customers to build and scale effective AI applications with OpenAI’s technologies. The Digital Natives segment serves technology and software companies that are building AI into the core of their products and businesses. These customers are often highly technical, move quickly, and are among the earliest adopters of OpenAI’s newest capabilities. Our Applied AI Engineers work directly with their engineering, product, and technical leadership teams to identify high-impact opportunities, solve complex technical challenges, and bring ambitious AI applications into production. About the Role We are seeking a Manager, Applied AI Engineering (Digital Natives) to lead the team responsible for the technical success of our most strategic technology and software customers in the Americas. In this role, you will lead a team of Applied AI Engineers who work hands-on with customers to design, build, evaluate, and scale AI applications. You will help determine where deep technical partnership can unlock the greatest customer and business impact, while developing repeatable approaches that allow the team to support a broad and fast-moving customer segment. As a manager, you will set the strategy and operating model for the team, coach and develop engineers, and serve as a senior technical partner to customers and internal stakeholders. You will work closely with Sales, Product, Engineering, and Research to connect what we learn from customers with OpenAI’s product direction and help customers take advantage of our newest capabilities. Success in this role will be measured by meaningful production applications, sustained adoption and usage, strong customer outcomes, and