Lead Systems Engineer in United States

About the Team The Growth team drives user and revenue growth across ChatGPT’s consumer and business segments as well as other OpenAI products worldwide. We operate across the full funnel - from awareness and acquisition through activation, retention, and expansion - using a combination of global performance marketing, AI-powered workflows, in-product optimization, insights, experimentation, and creative ops engineering. About the Role We are hiring a Lifecycle Lead to build the company-wide owned-channel capability that helps teams reach users with relevant, timely, and trustworthy experiences. This senior, hands-on leader will set the lifecycle strategy, partner with Engineering to build the orchestration and deployment platform, and establish the operating model that allows teams across the company to launch and improve evergreen programs safely at scale. You will sit at the intersection of platform, product, and campaign strategy. You will partner with Engineering, Product, Data Science, and Analytics on the underlying systems, and with Product Marketing Managers and other client teams to design journeys that help new, active, and returning users reach value and build durable habits. In this role, you will: Partner with product to set the company-wide vision, roadmap, and operating model for lifecycle and owned-channel engagement. Partner with Engineering, Product, Data Science, and Analytics to shape the tooling and infrastructure for identity, audiences, eligibility, consent, triggers, orchestration, decisioning, frequency, experimentation, localization, quality assurance, and observability. Define scalable deployment workflows—including self-service and centrally supported paths, intake, templates, approvals, governance, service levels, and incident response—so teams across the company can launch safely and efficiently. Partner with Product Marketing Managers and other client teams to translate audience, product, and business goals into evergreen journey stra

About the Team The ChatGPT Model Flywheel team unified goal is to transform model advancements into great ChatGPT user experiences through reliable serving, rapid experimentation, safe deployment, and continuous improvement. Team Focus Areas Model Experimentation: Enable rapid, safe model validation for ChatGPT and Codex products through experiment automation and lifecycle management. Model Deployment: Ensure safe, scalable deployment of model capabilities with robust rollout and operational tooling. Automate capacity management and incorporate platform-wide health monitors. Model Measurement: Build comprehensive evaluation and measurement systems for model quality, from user signals to launch scorecards. Improve end-to-end feedback loops for continual model improvement. Key Partnerships Collaborate cross-functionally with teams including Model Measurement DS, Research, Codex, Fleet, Inference, and API. In this role, you will: Elevate and consolidate ChatGPT’s harness, context management, and system prompt frameworks. Drive expansion and improvement of multi-tier model experiences. Support and scale self-serve experiment capabilities and automated guardrails. Lead model rollout automation, capacity management, and health monitoring. Shape end-to-end measurement systems (evals, grader signals, user feedback, etc.). You might thrive in this role if you have: Proven experience leading engineering teams in complex, cross-functional environments. Demonstrated success shipping production systems at scale (ideally for AI or large backend services). Deep understanding of model-driven product development, deployment lifecycle, and measurement tooling. Excellent communication and collaboration skills—experience interfacing directly with engineering, research, and product stakeholders. Prior involvement with large language models, distributed infrastructure, or experimentation platforms is a plus. Why Work With Us Tackle highly impactful technical challenges at the cutting edg

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 OpenAI is building the infrastructure foundation for the next generation of AI. The Data Center Engineering team defines the strategy, reference architectures, technical requirements, and delivery standards for the large-scale data centers that support OpenAI research, products, and infrastructure partners. As a Data Center Infrastructure Electrical Engineer, you will help define, validate, and scale the electrical power systems that support high-density AI compute. You will translate evolving compute requirements into practical facility and rack-power architectures, evaluate new technologies and vendor solutions, and drive technical decisions across design, manufacturing validation, construction, commissioning, deployment, and operations. This role is best suited for a senior hands-on engineer with deep experience in mission-critical power systems, strong judgment under ambiguity, and the ability to connect facility infrastructure, hardware requirements, controls, telemetry, reliability, and operations. About the Role We are seeking a senior electrical infrastructure engineer to lead the development of reliable, scalable, and efficient power architectures for high-density, liquid-cooled AI data centers. The ideal candidate has strong practical experience with critical electrical systems at data centers or comparable industrial scale, including medium-voltage and low-voltage distribution, utility interfaces, backup power, UPS and battery systems, rack power delivery, grounding, protection, controls, and monitoring systems. You should be comfortable moving between long-range architecture, detailed engineering review, lab validation, vendor qualification, field deployment, and operational troubleshooting. Key Responsibilities Design and optimize electrical topologies and equipment strategies that reduce cost, accelerate schedules, improve efficiency, increase scalability, and maintain high reliability and maintainability. Review and develop basis-of-des

About the Team OpenAI’s Industrial Compute team is responsible for building and scaling large-scale compute capacity across first-party data centers, strategic partners, and industrial infrastructure environments. We focus on converting power, land, hardware, and operational execution into reliable compute capacity that can support frontier AI training and inference workloads. This team operates at the intersection of infrastructure delivery, hardware systems, utilities, supply chain, and capacity strategy—ensuring OpenAI can scale compute faster than traditional models allow. About the Role We are seeking a Tokens-as-a-Service (TaaS) Lead to drive the end-to-end conversion of industrial-scale infrastructure investments into usable token capacity for OpenAI workloads. In this role, you will own execution across complex compute programs where raw infrastructure capacity must be transformed into operational GPU throughput. You will coordinate across data center delivery, power, networking, hardware deployment, workload enablement, finance, and external partners to ensure capacity becomes productive tokens as quickly and efficiently as possible. This role is ideal for someone who can bridge physical infrastructure delivery with compute utilization outcomes. Success requires strong systems thinking, elite program leadership, and the ability to drive accountability across internal teams and strategic partners. In this role, you will Lead Tokens-as-a-Service programs across industrial compute environments, including first-party and partner-owned capacity. Convert delivered power, space, and hardware capacity into production-ready token throughput. Build integrated execution plans spanning construction, power energization, rack deployment, networking, cluster readiness, and workload onboarding. Partner with infrastructure engineering, hardware, networking, finance, supply chain, and operations teams. Drive external providers, EPCs, OEMs, utilities, and strategic partners t

About the Team The Artifacts team is building the AI-native creation layer for documents, spreadsheets, slide decks, dashboards, reports, analyses, and new forms of interactive work products. We are rethinking what creation looks like when models can move from an ambiguous user goal to a polished, editable artifact with strong structure, taste, correctness, and speed. This is a high-agency team working across product, infrastructure, and research. We partner closely with model training teams to shape how frontier models create artifacts, and with ChatGPT product teams to turn those capabilities into experiences that millions of people can use. The work spans full-stack product engineering, model integration, rendering and editing systems, collaboration, storage, evaluation loops, and production reliability. Our ambition is to build the premier product experience for AI-generated artifacts: starting with familiar work products like slides, sheets, and docs, then expanding into new artifact types that are only possible in an AI-native world. About the Role As Engineering Manager, Artifacts, you will lead and grow the engineering team responsible for building this product and technical foundation. You will manage a team of full-stack and infrastructure-oriented engineers, set technical direction, and stay hands-on enough to shape architecture and debug hard problems. This role sits at the intersection of product engineering, research, and infrastructure. You will partner with researchers on how models are trained and evaluated for artifact creation, with product and design on the user experience. This is a strong fit for a technical manager who wants to build and ship, not only coordinate. The team has a fast trajectory, so you will help define both the product surface and the team that builds it. In this role, you will: Lead, manage, and grow a team building AI-native artifact creation experiences across documents, spreadsheets, slide decks, and emerging artifact form

About the Team The Demo Studio is responsible for translating OpenAI’s most advanced capabilities into tangible, high-impact experiences for customers. We design and deliver the demos, applications, and environments that define how executives understand what is possible with AI. Our work sits at the intersection of product, engineering, design, and go-to-market. We operate as a hybrid of product studio and live production team, building experiences that are both technically credible and narratively compelling. About the Role We’re looking for a Demo Studio Lead to own the end-to-end demo experience for OpenAI’s major events, webinars, and strategic programs. This is a highly cross-functional role focused on translating cutting-edge AI capabilities into clear, compelling, and production-ready experiences. You will own the full demo portfolio for an event or initiative, spanning mainstage moments, breakout experiences, booths, and supporting content. You’ll define the narrative, architect workflows, build high-fidelity demo environments, direct presenters, and ensure flawless execution in live environments. This is not a traditional sales engineering, presentation, or narrowly scoped design role — it requires a combination of product thinking, technical fluency, storytelling, systems design, and operational excellence. A key part of the role is presenting the work directly: delivering live demonstrations to executive, technical, and industry audiences across mainstage, breakout, customer, and recorded settings. This role is ideal for someone who thrives in ambiguity, operates with strong ownership, and is excited about shaping how the world experiences AI firsthand. This is a hybrid role that can be based in either San Francisco or New York. In this role, you will: Own the end-to-end demo experience across OpenAI-hosted summits, webinars, third-party industry events, and strategic executive demonstrations. Translate approved product positioning, real OpenAI capabiliti

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About The Role As a enterprise technical support engineer, you will work closely with our enterprise customers and engineers to resolve their most complex issues. You will also help build out systems and processes to manage tasks to completion. You will problem solve with our technical teams and work to resolve as much as you can while scaling our systems and support processes. This role will be based in San Francisco. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve Work closely with our largest customers providing white-glove support to solve the most challenging support interactions Build and maintain strong relationships with enterprise customers, ensuring high levels of engagement and satisfaction Lead the troubleshooting and resolution of advanced technical issues across Notion’s platform and embedded partner applications, with a focus on unlocking AI usage for customers Act as a bridge between your customers and Notion engineering

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Company Overview We are building the next generation of cloud security infrastructure, focusing on advanced Data Exfiltration Protection (DXP) and unified Data Movement Policies (DMP). Our mission is to provide seamless, context-aware security that protects sensitive data without hindering developer velocity. We are looking for a visionary Principal Engineer to lead the technical strategy and architecture for our Data Movement and Perimeter control systems. Role Summary As a Principal Engineer in the Data Protection group, you will be the technical lead for the Data Exfiltration Protection (DXP) and Data Movement Policy (DMP) initiatives. You will bridge the gap between high-level security policy and low-level system enforcement, ensuring that our perimeter controls are robust, scalable, and deeply integrated with context-aware access policy frameworks. You will be responsible for the architectural evolution of our egress control systems, moving from simple IP-based rules to sophisticated, content-aware, and identity-driven data movement governance. AS A PRINCIPAL SOFTWARE ENGINEER - IDENTITY, DATA SECURITY AND TRUST AT SNOWFLAKE YOU WILL: Architectural Leadership: Lead the design and implementation of the Data Movement Policy (DMP) framework, ensuring it can handle complex

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We’re hiring a talented Software Engineering Manager to lead the Snowtrail infrastructure team at Snowflake. Snowtrail is the infrastructure that enables Snowflake to deliver dedicated coverage for customer-specific workloads. Its innovative approach allows Snowflake to precisely test and measure the impact of changes on individual customers, making it essential for ensuring the platform’s reliability, correctness, and performance. Through query replay, Snowtrail helps us catch regressions early. By leveraging machine learning models to intelligently sample queries and workloads, we continuously optimize for both cost and performance. Evolving Snowtrail to incorporate new engine features while improving scalability, efficiency, and reliability is central to our continued success OUR IDEAL MANAGER WILL HAVE : Strong passion and proven track record for shipping quality software in high code velocity environments 10+ years industry experience designing and building distributed data systems. Excellent problem solving skills, and strong CS fundamentals including data structures, algorithms, and distributed systems. Fluency in SQL, Java, C++, Python or Go. Ability to collaborate well across teams, build high-performing teams and mentor junior engineers. Excellent interpersonal co

Job Details: Job Description: The Role and Impact As a Module Engineer, you will play a pivotal role in enabling Intel's cutting-edge manufacturing processes by ensuring the seamless operation and optimization of critical high-volume equipment. Your day-to-day responsibilities will focus on conducting tests, measurements, and maintenance activities to ensure the equipment meets stringent safety, quality, and efficiency standards. By driving process improvements and collaborating with global teams, you will contribute to the successful production of advanced integrated circuits and help shape technological innovation in the semiconductor industry. Business Group You will be part of Intel's Manufacturing and Operations organization, which is central to Intel's mission of creating world-changing technology. The group specializes in scaling advanced manufacturing techniques, ensuring high product quality, and delivering cost-effective solutions that support Intel's growth. Through its close collaboration with global teams, this organization fosters technological innovation and operational excellence across Intel's manufacturing sites worldwide. Key Responsibilities - Conduct equipment tests and measurements to ensure control over critical dimensions, registration and defectivity of the production line. - Recommend and implement modifications to improve production efficiency, manufacturing techniques, and output quality. - Own and execute maintenance and repair activities for manufacturing equipment, ensuring minimal downtime. - Lead continuous improvement initiatives for safety, quality, cost, productivity, defects, and yield metrics. - Collaborate with equipment suppliers to enhance manufacturing tools and processes. - Develop and optimize systems for preventing excursions and detecting process or equipment discrepancies. - Participate in technology transfers t

We at NVIDIA seek an Senior Developer Relations, Automated Synthetic Chemistry Science Lead who can coordinate science streams. This role exists at the crossroads of experimental science, optimization, analytical characterization, AI modeling, laboratory automation, and data infrastructure. It demands a practitioner with a background in research who can lead interdisciplinary science teams and accelerate experimentation without compromising scientific quality. What you'll be doing: Coordinate the operating plan across research priorities, technical execution, and program achievements. Convert research objectives into experimental priorities, parameter-space development, campaign planning, and success criteria. Lead research initiatives encompassing synthetic chemistry, catalysis, process chemistry, machine learning, automated systems, and data processing. Build standardized experimental traces capturing successful and unsuccessful outcomes, metadata, quality-control signals, analytical summaries. Guide AI systems for feasibility assessment, outcome prediction, optimization, scope exploration, and campaign orchestration. Integrate automated experimentation, analytical data streams, data curation, model retraining, and campaign decisions into a closed-loop operating model. Establish science-stream governance: build reviews, decision logs, risk and dependency tracking, quality thresholds, and paths for addressing blocking issues. Prepare recurring workstream readouts for program leadership, including scientific progress, critical decisions, cross-team dependencies, resource needs, and unresolved risks. What we need to see: PhD (or equivalent experience) with 10+ years of hands-on experience in experimental science, chemical engineering, material science, robotics, a

Job Details: Job Description: The Role and Impact We are seeking a Module Engineer to play a pivotal role in advancing Intel's high-volume manufacturing capabilities. In this position, you will oversee critical equipment and processes that enable the production of cutting-edge integrated circuits, driving innovation in device miniaturization and semiconductor excellence. Your expertise will directly impact production efficiency, quality, and yield, ensuring Intel maintains its leadership in the semiconductor industry. Business Group Join Intel Corporation's Engineering team, which is dedicated to enabling the rapid advancements of semiconductor manufacturing technologies. This group supports Intel's broader mission of delivering world-class technology solutions by optimizing manufacturing processes, ensuring high-quality outputs, and transferring technology globally. As part of this team, you will collaborate across regions to shape the future of semiconductor innovation. Key Responsibilities - Operate and optimize high-volume manufacturing equipment and processes to maintain control over critical dimensions and defectivity. - Conduct tests and measurements to evaluate equipment and process performance, recommending and implementing modifications to improve productivity and quality. - Execute maintenance, repair, and upgrades for assigned equipment and modules to ensure consistent operational excellence. - Lead continuous improvement initiatives focused on enhancing safety, productivity, cost efficiency, and yield. - Develop and implement excursion prevention systems to detect and address discrepant materials or activities in equipment and processes. - Facilitate technology transfer to global manufacturing sites through training, audits, and documentation to ensure consistent processing across locations. - Oversee installation, conversion, and qualification of

Electronics Test and Evaluation Lab Technician (Senior or Lead) Company: The Boeing Company Boeing Defense, Space and Security (BDS) is looking for a Senior or Lead Electronics Test and Evaluation Lab Technician (Level 4 or 5) to join our team at the Starfire Optical Range on Kirtland AFB in Albuquerque, New Mexico. The role supports the Air Force Research Lab in their advancement of Space Domain Awareness capabilities using ground-based telescopes. Starfire Optical Range is a world class research facility with recognized achievements in adaptive optics, enabled by the quality, enthusiasm, and dedication of our entire team. Our team consists of engineers and technicians in all disciplines required to plan, design, integrate, and test complex optical, electronic, laser systems to achieve research objectives. Position Responsibilities: Plans, conducts and documents complex tests on products, systems, components, materials, and manufacturing processes and technologies. Designs, fabricates, builds and analyzes test systems, materials, components, software and methodologies. Coordinates test requirements, determines test methods and capabilities. Conducts system test preparations by guiding system integration, fabrication, modification, setup, checkout and teardown. Performs test article configuration control. Conducts complex tests, analyzes data and documents results; participates in test readiness reviews. Identifies and resolves test anomalies. Troubleshoots and resolves complex laboratory and test-related problems. Coordinates test laboratory activities, maintenance and repairs, and

We are seeking an experienced Senior Generative AI Developer to help drive the design, development, and integration of state-of-the-art Generative AI and agentic AI solutions across our enterprise Controls Technology platform. You will collaborate with cross-functional teams, contribute deep technical expertise in context engineering, retrieval systems, knowledge graphs, and multi-agent orchestration, and play a key role in delivering scalable, grounded AI solutions to enhance automation and operational efficiency. This role centers on architecting robust applications and agent systems on top of pre-trained and hosted foundation models — not on training or fine-tuning models. Key Responsibilities Collaborate with AI architects, leads, and stakeholders to design and implement generative and agentic AI solutions that address business challenges. Architect advanced context engineering strategies — context layering, chaining, compression, pruning/offloading, and memory management — to maximize reliability, provenance, and token efficiency in production. Design and implement advanced generative AI methods, including sophisticated prompt engineering and Retrieval-Augmented Generation (RAG) . Build and optimize RAG systems , including hybrid search, multi-vector retrieval, and re-ranking pipelines. Design and implement knowledge graphs and Graph RAG architectures to enable multi-hop reasoning, explainability, and traceable, grounded responses for high-value business domains. Architect agentic workflows and multi-agent systems using Google Agent Development Kit (ADK) and comparable frameworks (LangGraph, Microsoft Agent Framework, CrewAI), applying orchestration patterns such as supervisor/worker, hierarchical, and peer-to-peer. Design robust agent harnesses — governance, constraints, feedback loops, state/session management, and