Lead Systems Engineer in United States

About the Role The Electrical Commissioning Lead owns electrical commissioning planning, readiness, quality coordination, and test execution oversight for the project. This role ensures electrical systems are inspectable, testable, safe to energize, and ready for coordinated functional and integrated systems testing. Reports to the Commissioning Project Lead and partners closely with electrical contractors, equipment vendors, design/engineering teams, the mechanical commissioning lead, controls stakeholders, and vendor field/test engineers. Key Responsibilities Develop and maintain the electrical commissioning scope, readiness criteria, inspection strategy, and test execution plan. Review electrical design packages, specifications, submittals, method statements, sequence assumptions, and testing requirements for commissionability and risk. Coordinate electrical QA/QC inspections with contractors and vendor field/test engineers, including installation checks, pre-functional readiness, deficiency capture, and closeout tracking. Own electrical commissioning procedure development and review, including startup, energization readiness, functional testing, failure mode validation, controls interfaces, and integrated systems testing inputs. Coordinate with equipment vendors on factory/site acceptance requirements, startup support, test prerequisites, documentation packages, and vendor participation during critical tests. Support energization planning, switching and safety coordination, access sequencing, temporary conditions, witness points, and hold points. Lead discipline-level review of electrical test results, deficiencies, corrective actions, retest requirements, and acceptance evidence. Maintain electrical commissioning dashboards and status inputs for the Commissioning Project Lead, including risk items, resource needs, test readiness, and issue aging. Partner with the Mechanical Commissioning Lead on cross-discipline dependencies, including controls, life safety int

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Senior Software Engineer Job Overview: Responsible for the analysis, design, development, testing, and delivery of secure, scalable software solutions. Define requirements for new applications and customization adhering to Mastercard standards, processes, and best practices. Develop, customize, and test applications to integrate to Mastercard specifications. Provide leadership, mentoring, and technical training to other team members. Major Accountabilities • Plan, design, architect, and develop secure, scalable, and maintainable technical solutions and alternatives to meet business requirements in adherence with Mastercard standards, processes, and best practices • Lead day-to-day system development and maintenance activities of the team to meet service level agreements (SLAs) and create solutions with a high level of innovation, cost effectiveness, quality, reliability, and faster time to market. • Accountable for the full systems development life cycle including creating high-quality requirements documents, use cases, designs, and other technical artifacts including but not limited to detailed test strategies, performance benchmarking, release rollout and deployment plans, contingency/back-out plans, feasibility studies, cost and time analysis, and detailed estimates. • Design, develop, test, dep

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. Security Engineering is the engineering function inside the Plaid security org that focuses on developing the industry-leading security systems and infrastructure. Security Engineering owns most of Plaid’s security-related infrastructure: secure data storage, key management systems, internal identity platform, internal authentication systems, internal permission management, and internal authorization service. We develop solutions across data encryption, key management, access control, and data loss prevention to protect sensitive consumer data. We believe in the Zero Trust security model and are always looking for ways to improve our authentication and access control platforms. About the role: You will develop security capabilities to secure Plaid infrastructure and sensitive data access. You will lead the team’s strategic planning in collaboration with the manager and other senior engineers. You will own, maintain, and build Plaid’s security infrastructure and services like IAM Gateway, Key Management System and Network Firewall. You will consult with product engineers to ensure Plaid services meet security standards. You will help educate and support other engineering teams to improve security in

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We’re looking for a Rack Power Engineer with deep expertise in high-power conversion and distribution to design, qualify, and support power systems for AI supercomputers. You will own rack power solutions—including power shelves, AC/DC rectifiers, power supply units (PSUs), power management controllers (PMCs), and high-current distribution—from requirements and supplier development through deployment. You will also monitor fleet rack power health, lead debugging and root-cause investigations, and drive improvements into hardware, firmware, and qualification coverage. 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 rack power architecture and requirements for high-power AI supercomputing systems, including power budgets, AC input interfaces, DC distribution, redundancy, efficiency, serviceability, and integration with data center infrastructure. Drive the design and supplier development of power shelves, rectifiers, PSUs, PMCs, busbars, connectors, and protection circuits. Review electrical designs and control behavior, and evaluate performance, cost, reliability, and availability trade-offs. Define and execute component, shelf, and rack qualification plans covering load transients, current sharing, hot-swap, startup and shutdown, redundancy failover, fault protection and recovery, thermal limits, and AC disturbances and ride-through

We are investing in agentic AI and need a Senior AI Engineer to lead the design and delivery of these systems. This is a foundational hire: you will own both the agent-facing workstreams — pipelines, orchestration, conversational interfaces — and the underlying context layer that makes them reliable, including memory management, knowledge graph integration, and retrieval infrastructure. You will work closely with data engineers, project leads, and client stakeholders, and play a key role in shaping how Lynx builds and ships AI solutions at scale. What This Involves: Lead the architecture and delivery of agentic AI systems end-to-end: agents, orchestration, tool use, and multi-step reasoning workflows. Own the context layer: design and implement memory architectures (episodic, semantic, working memory) and integrate GraphRAG and knowledge graph retrieval into agentic pipelines. Build robust RAG systems — including vector retrieval, graph traversal, and hybrid search — and ensure retrieval quality through evaluation frameworks. Translate client requirements into technical designs, presenting approaches and trade-offs to both technical and non-technical stakeholders. Define standards and reusable patterns for agentic AI development that other engineers at Lynx can build on. Set up observability, evaluation, and monitoring pipelines to ensure AI systems perform correctly in production. Requirements: 5–8 years of software or ML engineering experience, with at least 2–3 years building LLM-based or agentic AI systems in production. Deep hands-on experience with agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, or similar) and LLM APIs (OpenAI, Anthropic, etc.). Strong understanding of agent design patterns: ReAct, planning loops, tool use, multi-agent coordination, and memory architectures. Practical experience with GraphRAG or knowledge graph-based retrieval (e.g., Neo4j, Microsoft GraphRAG) and vector databases (Pinecone, Weaviate, Qdrant, etc.). Proficiency in

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role As a software engineer on the AI Soltuions team, you will co-lead customer engagements with an AI Solutions Strategist . The Strategist owns business discovery, ROI narrative, stakeholder alignment, and rollout planning. The engineer owns technical discovery, solution design, prototyping, implementation, and production readiness. This is a deeply client-facing role. You will spend significant time with customers and end users, moving projects from bootcamp and workflow discovery through implementation, launch, and steady production usage. What You’ll Do Translate customer goals into clear system requirements and non-functional requirements covering security, privacy, reliability, performance, scalability, and cost. Partner directly with customers to understand current workflows, constraints, systems, data quality, and adoption blockers. Create and maintain solution architecture artifacts: System context and data flow diagrams Integration plan across Ramp and customer systems Security model covering permissions, access patterns, and au

About the Team Training Runtime builds the distributed systems that power OpenAI's largest model training runs - most recently GPT-5.5! The Data Movement area owns the infrastructure that keeps training jobs supplied with the right data at the right time, and keeps model state moving safely and efficiently across large clusters. Our work spans machine learning systems, distributed storage, high-throughput data loading, reliability engineering, and developer experience. Success means researchers can move quickly while training runs remain fast, reproducible, debuggable, and resilient at scale. About the Role We are looking for a deeply hands-on Technical Lead Manager to own datasets throughout our training infrastructure. This person will set the direction for how training jobs read data: the APIs, storage contracts, versioning model, benchmarks, debugging tools, and reliability guarantees that make data access consistent across current and future training frameworks. You will begin as the primary technical owner for dataset reads, working directly in the code while aligning researchers, training framework owners, storage teams, and infrastructure partners around a durable platform. The problem is deceptively hard at frontier scale: make enormous, heterogeneous datasets easy to consume, correct across distributed workers, observable when something goes wrong, and flexible enough to support pretraining, reinforcement learning, and multimodal training. In this role, you will Design and build a unified dataset read platform for multiple current and future training frameworks. Define dataset APIs, storage-format expectations, registration/versioning, and migration paths that make data access reproducible and maintainable. Build reliability into the read path, including stateful iteration, caching, fast restart, recovery, and clear operational contracts. Build terminal and web-based visualizers that let teams inspect text, multimodal, and reinforcement learning data late

About the role We’re looking for an engineering manager to lead a team building software systems that detect and prevent harmful misuse of frontier AI models—before incidents occur. This is a builder’s role: you’ll lead engineers shipping production services, detection pipelines, and mitigation mechanisms that protect frontier model integrity and reduce high-severity misuse risk. While this work intersects with frontier model development, security and risk, we’re explicitly seeking someone with a software engineering foundation who is comfortable building reliable systems that can operate at billions of users scale. In this role you will: Lead a team of software engineers building detection + mitigation systems for frontier model misuse, with an emphasis on model IP protection / distillation detection and emerging risk surfaces from autonomous agents. Set the technical roadmap and execution strategy: prioritize, design, ship, iterate, measure impact. Build production systems: services, pipelines, tooling, instrumentation, and automation that scale with frontier model usage. Partner deeply with Research and Product to translate evolving model capabilities into concrete tests, signals, and mitigations that can be deployed at scale. Drive strong engineering fundamentals: architecture, reliability, monitoring, performance, and operational excellence. Hire and grow an exceptional team across backend, data systems, and applied ML engineering domains as needed. Anticipate what breaks at scale as agentic workflows become more capable. You might thrive in this role if you: Experience building systems in adversarial, fast-evolving environments Are comfortable with ambiguity and novelty Have experience adjacent to security (e.g., abuse prevention, fraud, integrity, platform defense, auth/identity, malware/spam, adversarial environments) Communicate clearly and build trust quickly with senior stakeholders—pragmatic, collaborative, and calm under scrutiny. Significant experience

About the Team The Support team is central to ensuring that our customers' experience with our products is nothing short of exceptional. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others to deliver the best possible experience to our customers at scale. OpenAI's customers represent a range of diverse backgrounds and maturity, from individual customers to early-stage startups and established global enterprises. Given OpenAI’s breakneck shipping cadence and growth – and the expectation that it will only accelerate – our ability to architect automation systems and agentic workflows for scale is central to our ability to maintain exceptional support quality in the face of AGI. About the Role We are seeking a Support Operations Lead who combines operational leadership, systems thinking, vendor management, and hands-on execution. You’ll own service health, automation programs, partner and vendor management. In addition to delivering high-quality service, you’ll identify opportunities to reduce manual work, experiment with tools and help operationalize AI across support at scale. This is not a traditional support operations lead role. We’re looking for someone to help us define the future of support, who thrive at the intersection of team/project management, systems building, data science/engineering, and with deep craft experience in the support operations space. 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: Lead and evolve organizational design for our frontline operations across partner and vendor management, coaching teams to expand automation and deliver measurable capacity gains. Lead multi-site partner management, including commercial ownership, capacity planning and workfor

About the Team OpenAI’s User Operations team shepherds our customer’s adoption of AI and ensures that our customers' product experience is nothing short of exceptional. We are building the very first post-AGI support team. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others to deliver the best possible experience to our customers at scale. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. About the Role We are looking for a leader to build and scale our Support Engineering team, which will collaborate directly with our strategic enterprise accounts, our product and engineering teams, as well as our field teams to solve some of the most difficult technical problems faced by our customers. You will lead one of the best technical troubleshooting teams at OpenAI, and our customers and Engineering teams will look to you for technical guidance in addressing the most technically difficult issues in our environment. You will play an integral role in building knowledge within the team and be part of strategic initiatives for organizational and process improvements. Working directly with our most strategic customers - You will be crucial to the success of the most innovative, disruptive, and high-scale AI solutions being built with the OpenAI platform. This team will handle high difficulty situations and issues. The team will be global, providing 24x7 technical coverage for our customers. This will be an opportunity to build this new team from first principles - your leadership will determine the future of this organization. The ideal candidate will have a combination of technical capabilities mixed with strong leadership and systems building strength. This role is based in San Francisco, CA. We use a hybrid work model of 3 days

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the Role A strong and reliable platform is essential to scaling Sentry for the future. Our Platform organization is responsible for everything that powers Sentry—from cloud infrastructure and streaming systems to storage, deployment, and security. We own the core services and technical foundations that enable every product and engineering team at Sentry to move fast and build with confidence. We're looking for a passionate and pragmatic Senior Staff Software Engineer to help lead this evolution. In this role, you’ll report directly to the VP of Engineering and collaborate with teams across the company to shape the future of Sentry’s platform. What You’ll Do Architect the future of Sentry by translating business needs and product strategy into clear, scalable technical blueprints. Partner with product and engineering leaders to align technical roadmaps with company goals. Lead cross-cutting initiatives across the Platform org—owning them end-to-end and driving meaningful outcomes. Promote engineering excellence by mentoring platform engineers, sharing best practices, and setting high standards for system design, scalability, and operational quality. Review major architectural proposals and help ensure consistency, maintainability, and long-term technical health across the company. You’ll Love This Job If You... Enjoy designing and building platforms that help teams move faster and scale safely. Thrive on solving complex, multi-dimensional problems across product, infrastructure, and organizational layers. Want to make architectural decisions that shape Sentry’s long-term success. Bring new ideas, tools, and frameworks t

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in New York. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript, or c

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript,

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in Seattle. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript, or co

About the Team The Growth Platforms team builds the systems and operating foundations that help OpenAI grow responsibly. We partner across the product portfolio to connect customer signals, identity and consent, campaign workflows, measurement, and product experiences into an AI-enabled growth engine. Our work helps teams launch, learn, and scale with a high bar for data quality, privacy, reliability, and customer trust. About the Role We’re looking for an experienced marketing technology and operations leader to drive cross-functional work at the intersection of growth, measurement, data, and automation. Your mission will be to turn fragmented tools, signals, and workflows into reliable, measurable, AI-enabled capabilities that teams can use safely at scale. You’ll work across Growth, Marketing Operations, Product, Engineering, Data Engineering, Data Science, Security, Privacy, Legal, and Revenue Operations, as well as external advertising platforms, measurement providers, and implementation partners. You’ll translate business requirements and privacy constraints into data contracts, integration designs, rollout plans, and reliable first-party data systems. This is a hands-on, high-impact role for someone who brings structure to ambiguity and moves from event schemas, APIs, and data quality assurance to operating cadences, partner enablement, and executive updates. This role is based in San Francisco or New York City with a hybrid office expectation. In this role, you will: Own the operating model for Growth’s marketing technology stack across identity, consent, audiences, activation, measurement, and experimentation. Own and operate the complete paid-media tracking and measurement system, including website pixels, server-to-server conversion events, mobile measurement integrations, identity and consent controls, attribution methods, and timely signal delivery to advertising platforms. Design and implement event schemas, data mappings, APIs, and integrations; valid