About the team The Applied AI Engineer - Digital Natives team is responsible for ensuring the safe and effective deployment of Generative AI applications for developers and enterprises. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of frontier AI use cases for their industry and drive them to production through strong technical guidance. As an Applied AI Engineer in the Digital Native segment, you’ll help large and highly sophisticated companies transform their business through custom AI solutions applications such as customer service, automated content generation, contextual search, personalization, and other novel use cases leveraging OpenAI’s newest, most exciting models and latest capabilities. About the role We are looking for a driven solutions leader with a product mindset to partner with our customers and ensure they achieve tangible business value with frontier AI. You will pair with senior customer leaders to establish AI strategic roadmaps and identify the highest value applications. You’ll then partner with their engineering and product teams to move from prototype through production. You’ll take a holistic view of their needs and design an enterprise architecture using OpenAI APIs and other services to maximize customer value. You will collaborate closely with Sales, Solutions Engineering, Applied Research, and Product. This role is based in our SF or Seattle office. 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: Deeply embedded with our most sophisticated and technical platform customers, serving as their technical thought partner in ideating and building novel applications on our APIs. Proactively provide guidance to our customers on how to maximize business impact from their applications, accelerating their time to value. Experiment and prototype solutions with and for your customers. Forge and manage relat
Jobs in United States
Engineering Lead Analyst in United States
2,854 active opportunities · Updated October 2026
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Explore current engineering lead analyst jobs across United States. Filter by work mode, employment type, experience, department, date posted and distance.
About the Team The GPT Infrastructure team builds systems that turn advances in model inference and optimization into reliable production capabilities. We enable OpenAI workloads to be qualified and optimized across new accelerator platforms without requiring a one-off port and tuning effort for every hardware target. Our work spans distributed systems, model execution, compilers and runtimes, performance engineering, secure partner integrations, evaluation systems, and developer tooling. We build the infrastructure that makes optimization workflows automated, reproducible, and trustworthy. About the Role We are seeking a software engineer to help build the platform that qualifies and optimizes inference workloads across heterogeneous compute environments. You will develop both OpenAI-hosted services and secure partner-side software for running long-lived optimization workflows. These workflows generate candidate kernels, runtime configurations, and serving-stack changes; compile and execute them on target hardware; verify their correctness; measure their performance; and use the results to guide further optimization. You will work across model architecture, distributed execution, compilers, runtimes, networking, and accelerator systems. A central part of the role is turning research prototypes and one-off hardware bring-up efforts into reliable, reusable infrastructure with clear contracts, reproducible results, strong observability, and well-defined security boundaries. Key Responsibilities Design, build, and operate APIs and control-plane services for long-running workload qualification and optimization campaigns, including scheduling, retries, checkpointing, resource budgets, and observability. Build secure partner-side execution and evaluation software that can compile, run, verify, profile, and benchmark candidate artifacts on accelerator hardware. Integrate model workloads, hardware profiles, compiler toolchains, runtimes, serving engines, and distributed-exe
About the Team We’re hiring software engineers to make OpenAI’s Model Performance teams more productive. These teams work on the systems, tooling, and infrastructure that help improve model performance across OpenAI’s training and inference workloads at frontier scale. About the Role We’re looking for an autonomous, high-ownership developer productivity engineer who cares deeply about helping other engineers move faster, safer, and with more confidence. This role will sit within OpenAI’s Model Performance organization, contributing to developer infrastructure, CI systems, testing workflows, tooling, and broader performance infrastructure efforts. There is also a strong opportunity to contribute to the Triton project and help improve the systems that support performance-critical engineering work across OpenAI. In this role you will: Improve development workflows for engineers working on model performance infrastructure Design and improve CI/CD, release, validation, and testing pipelines Build and maintain tools that improve reliability, iteration speed, and engineering confidence Partner closely with engineers to identify friction in testing, debugging, deployment, and development workflows Contribute to infrastructure efforts that support performance-critical training and inference systems Help improve developer experience across Python-heavy codebases and performance-oriented infrastructure Work in a high-context, ambiguous environment where ownership and good judgment matter You might thrive in this role if: You are motivated by enabling the people around you and helping engineers do their best work You have strong experience with CI/CD, developer infrastructure, testing systems, tooling, or build/release workflows You are highly collaborative, empathetic, and comfortable partnering deeply with technical teams You are strong in Python and enjoy building reliable, scalable developer tools and infrastructure You have experience improving large-scale engineering work
About the Team The Codex Core Agent team builds the kernel of Codex. We own making the agent better, accelerating research, and making those improvements real in production for our users. That means working across the systems that make Codex actually function as an agent in the real world: the production performance envelope around tokens, latency, reliability, cost, and capacity; the core execution loop and interfaces that turn models into useful behavior; the shared infrastructure that enables other teams to build on Codex; and the feedback loops that turn real-world usage into better models and better agent behavior over time. About the Role We’re looking for applied AI engineers to help bring Codex agents from impressive demos to dependable tools. This role is about improving agent performance on real software engineering tasks and closing the gap between research capability and real-world usefulness. You’ll work closely with research, infrastructure, and product to ensure agents are not just powerful, but useful, steerable, and reliable in practice. The job is not only to improve model behavior in isolation, but to turn those improvements into measurable gains in solve rate, usefulness, and economic value for users. What You’ll Do Design and iterate on agent behaviors across real-world coding tasks and long-horizon workflows. Work closely with research to develop and run evals to measure agent performance, regressions, failure modes, and edge cases. Improve performance through prompting, tool-use strategies, context construction, and model-facing experimentation. Analyze failures in production and systematically improve robustness and reliability. Build feedback loops and data systems that get better real-task data into evaluation and research. Work with product teams to shape user-facing agent experiences and the interfaces the agent depends on. Help define what “good” looks like for agents completing complex tasks end-to-end. You Might Be a Good Fit If You Ha
About the Team The Future of Computing Research team is an applied research team within the Consumer Devices group focused on developing new methods, models, and evaluation frameworks that support our vision for the future of computing. We work at the frontier of multimodal AI, helping turn emerging model capabilities into product experiences that are useful, delightful, and worthy of long-term trust. Our work explores a new class of AI systems that can learn over time, adapt to individuals, and support people in the flow of daily life. This includes long-term memory, user modeling, and personalization systems that are aligned not just with immediate satisfaction, but with a person’s broader goals, values, and well-being. We work closely across research, engineering, design, product, and safety to define what it means to build AI systems that know you over time, act at the right moment, and help in ways that are context-aware, respectful, and demonstrably beneficial. About the Role We are looking for a Research Engineer / Scientist to join the Future of Computing Research team to work on RLHF and post-training for personalized, multimodal AI systems. This role will focus on building the learning and evaluation foundations that help models become more context-aware, adaptive, and useful over time. You will work on problems such as reward modeling, preference learning, long-horizon evaluation, and policy improvement for systems that must make high-quality behavioral decisions in realistic user settings. The work is deeply product-grounded: success is not just higher benchmark performance, but better model behavior in real-world use. The ideal candidate is excited about pushing beyond one-turn assistant behavior toward systems that improve through feedback, learn from richer signals, and are trained against meaningful notions of user value. Internally, that maps closely to the need for careful reward design, feedback loops, and evaluation frameworks that test whether i
About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role We’re seeking an exceptional Staff - Principal level offensive security domain expert to build agents that continuously identify and coordinate remediation of vulnerabilities across OpenAI’s infrastructure and applications. You will be the technical owner of this effort, combining deep offensive security judgment with agent engineering to build a production system that can operate safely and reliably at scale. As OpenAI increasingly uses automation throughout the company, we believe our security testing must become increasingly automated as well. Advances in model capabilities create an opportunity to test more of our attack surface than would be possible through human effort alone and a need to ensure that we remain ahead of those same capabilities as they become available to attackers. In this role, you’ll build a portfolio of specialized agents that develop a deep understanding of OpenAI’s infrastructure, applications, processes, and security boundaries. These agents will combine internal context with feedback from running systems to explore our cloud environments, Kubernetes clusters, web applications, endpoints, external attack surface, and other high-value targets. The goal is for agents to not only discover vulnerabilities, but also to validate exploitability, document impact, drive remediation, and verify fixes. Success will be measured through outcomes like vulnerabilities fixed, attack surface covered, and performance on evals
About the Team: The OpenAI API team builds the foundation that enables every developer to harness OpenAI’s models safely, reliably, and at scale. We design and operate the systems that power model serving, API access, billing, developer tooling, and enterprise integrations—forming the connective tissue between OpenAI’s research breakthroughs and real-world products. Our mission is to make it effortless for anyone to build with OpenAI technology. We’re responsible for the infrastructure and product layers that allow millions of developers to integrate GPT models, fine-tune behavior, manage data, and deliver transformative experiences to their users. We collaborate across product, research, and engineering teams to ensure that innovation in model capabilities translates directly into value for customers. The API team spans multiple disciplines, including product management, infrastructure engineering, developer experience, and data systems. We care deeply about reliability, scalability, and simplicity—creating tools that let developers focus on their ideas while we handle the complexity of running world-class AI systems. About the Role: We are seeking an experienced Product Manager to define and scale the construction of our data processing, data privacy, billing, and access controls products. You will set strategy and execute on projects like expanding our regional data processing footprint, enabling new inference caching controls in the API or building APIs that make it easier for organizations to manage their spend limits. You will also define the strategy and ship foundational capabilities that ensure customers use OpenAI products securely, privately, and with enterprise-grade controls. This role partners deeply with engineering, security, legal, compliance, finance and leadership to deliver high-trust, enterprise-grade systems. 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 n
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 are looking for a systems-minded engineer to help advance our kernel development, performance engineering, and hardware-software co-design capabilities, with a particular focus on AI-assisted workflows and tooling. This person will work at the intersection of kernel optimization, developer tooling, observability, and research infrastructure, helping us improve both how production kernels are built and optimized, and how future hardware-software systems are designed and evaluated. The role is ideal for someone who is excited by low-level performance work, but also sees AI and automation as powerful tools for accelerating engineering velocity. You will help define the future of kernel engineering in the era of AI-assisted development. In this role, you may: Build developer tooling and workflows that make kernel development and performance optimization faster, more scalable, and easier to debug, integrate, and deploy. Develop observability, diagnostics, and validation infrastructure that makes AI-assisted optimization systems more interpretable, reliable, and effective. Optimize production kernels end to end by formulating optimization problems, running search loops, analyzing bottlenecks, debugging generated implementations, and landing improvements into production. Design abstractions, interfaces, and automation systems that accelerate kernel optimization, correctness validation, and hardware-software co-design. Improve AI-assisted optimization systems for sp
About the Team The Statsig team within OpenAI builds the experimentation, feature rollout, dynamic configuration, and analytics systems that help OpenAI ship products with speed, safety, and evidence. Our work sits on the critical path for how product, engineering, research, and go-to-market teams learn from real-world usage and make high-confidence decisions. Statsig began as an independent company focused on helping builders move faster through trustworthy experimentation and feature management. After Statsig joined OpenAI, the team began the next chapter: bringing that deep product expertise, customer intuition, and mature platform infrastructure into OpenAI as the experimentation and rollout platform for every product we ship. Today, we support teams across ChatGPT, Codex, model measurement, consumer experiences including ads, business subscriptions, developer products, and the shared infrastructure that connects them. These teams rely on Statsig to safely introduce new capabilities, compare product and model behavior, measure impact, and roll changes forward or back with confidence. We are at a defining moment in the platform journey. OpenAI has the data, product surface area, and pace of innovation to learn faster than almost any organization in the world, but that potential only becomes real if teams can experiment responsibly, measure clearly, and roll out changes safely. Adoption of the platform is accelerating rapidly across the company, and recent SDK and server-side infrastructure work has already produced measurable wins in latency, reliability, memory usage, and compute efficiency for important services. Based out of OpenAI’s Bellevue office, we are a close-knit team that values in-person collaboration, urgency, craft, and impact. We build for other builders, and the best version of this team is one where every OpenAI product team can move faster because the experimentation and rollout layer is dependable, fast, and easy to use. About the Role We are l
About the Team Governance, Risk, and Compliance (GRC) is foundational to Security delivering mission outcomes at OpenAI. We’re excited about building creative solutions to ambiguous security requirements and delivering new technologies to mission critical customers. The GRC team provides security and engineering expertise to ensure our customers’ most critical and stringent requirements are met. We are technical in what we build but are operational in how we do our work, and are committed to obtaining, expanding, and maintaining Authorizations to Operate (ATOs) for critical systems while fostering a collaborative and execution-driven culture. About the Role Our technologies support some of the most important and impactful work in the world, including our strategic and high-impact customers in the public sector. As a GRC Program Manager, you’ll play a pivotal role in achieving US government (USG) ATOs and compliance frameworks, including but not limited to FedRAMP and Department of War (DoW),for OpenAI products and support agency-specific ATOs for systems deployed in highly regulated and secure environments. You’ll work closely with engineers, internal stakeholders, and external assessors to design, document, and implement security controls that meet stringent compliance requirements. Your creativity and execution-focused approach will be critical in navigating complex challenges while maintaining the trust of our stakeholders. We’re looking for people who bring: Proven experience in obtaining and maintaining a FedRAMP ATO and agency specific ATOs in highly restricted environments, within government or regulated sectors. A deep understanding of USG security frameworks and policies (e.g., NIST, RMF, FedRAMP). Ability to communicate technical concepts to diverse audiences, including engineers and non-technical stakeholders. Exceptional technical program management skills, with the ability to multitask and deliver large complex programs under pressure. This role is base
$230K – $260K/yr
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 Millions of people rely on Notion to do their most important work, and protecting that trust is foundational to everything we build. We’re looking for a hands-on Detection Engineer to build and operate the systems and workflows we use to detect and respond to attacks across Notion’s cloud-native environment. You’ll ship high-signal detections, improve the platform that powers them, participate in incident response, and help shape how detection and response engineering scales at Notion. You’ll work closely with Engineering, Corporate Security, and Infrastructure, with broad latitude to identify gaps, prioritize investments, and build what’s needed next. We view detection and response as a software engineering discipline: detections are code, platforms are products, and measurement matters What You'll Achieve Design and maintain high-signal detections across cloud, identity, endpoints, and SaaS environments. Build and improve the detection platform, including rule lifecycle management, tuning, measurement, and rollout safety. Develop tooling and automation that accelerate triage, enrichment, investigation, and detection
ABOUT THE BRAND: Callaway Golf Company is a premium golf equipment, gear and apparel company with a portfolio of global brands, including Callaway Golf, Odyssey, TravisMathew, and OGIO. Through an unwavering commitment to innovation and premium craftsmanship, Callaway designs, manufactures, and sells high-performance golf clubs, golf balls, apparel, bags, and other accessories—setting the standard for performance in the game of golf. Our Mission: To create demonstrably superior and pleasingly different products powered by innovative technology and premium craftsmanship enabling golfers of all abilities to play their best and find more joy in the game. Our company is a blend of experience and diverse backgrounds, and together we look to leave the past behind while moving the game forward. For more information, please visit https://www.callawaygolf.com ** 6-month contract- (Maternity Leave Coverage) ** ROLES AND RESPONSIBILITIES: In conjunction with Director, Global Soft Goods Operations, translate design concepts and briefs to finished products using knowledge of customer preferences, product functionality, materials and manufacturing techniques. Work with Product Designer to translate critical features in working designs and techpacks to communicate to suppliers. Review and negotiate specific details during the sampling process related to design specifications. Review samples for execution accuracy, product functionality, cost engineering and manufacturing efficiency. Review product costing for accuracy and potential cost savings and work with Director and Product Manager to approve final costing. Review product and material te
We're looking for a Product Analyst to support our Point of Sale (POS) product team. You'll work closely with the POS Product Owner to translate business and venue needs into clear requirements, support day-to-day POS issues, and help drive continuous improvement of the POS platform across all venues. This role is a strong fit for someone who has spent real time in the trenches with POS systems, whether building them, configuring them, or supporting the people who use them every day, and who wants to move deeper into product-facing work. What You'll Do Partner with the POS Product Owner to gather, document, and prioritize requirements for POS enhancements, integrations, and fixes Analyze POS support tickets and incident trends to identify recurring issues, root causes, and opportunities for product improvement Translate business and venue operations needs into clear user stories, acceptance criteria, and functional specifications Support testing and validation of new POS features and releases, including UAT coordination with venue stakeholders Serve as an escalation point for complex POS issues, working with engineering, support, and vendor teams to drive resolution Monitor POS system performance and data quality, flagging anomalies that could affect transactions, inventory, or reporting Maintain and update product documentation, release notes, and training materials for interna
The Manager, Business Intelligence leads a team of product owners and reporting engineers who build and maintain the reporting our corporate business areas and venues run on. You set the standard for how data is modeled, defined, and delivered in Amazon Quick Suite (Quick Sight) on top of Redshift and Snowflake, and you connect two halves of the team: the product owners who own the relationship with the business and the backlog, and the engineers who build against it. Success is measured less by dashboards shipped and more by decisions improved — how fast a venue GM or a corporate leader gets a reliable answer, and how much they trust it. Team leadership Lead, coach, and develop a team of BI product owners and reporting engineers; own hiring, onboarding, performance, and career growth across two distinct skill tracks. Develop product owners in requirements gathering, backlog management, stakeholder communication, acceptance criteria, and saying no well. Develop reporting engineers in SQL, data modeling, Quick Suite development, and engineering craft. Hold the line between the two: ensure requirements arrive well-defined and that engineers aren't absorbing unscoped work mid-sprint. Run the team's delivery cadence — intake, prioritization, sprint or release planning, and demo/review — balancing executive asks against roadmap commitments and technical debt. Establish and enforce team standards for SQL, data modeling, version control, code review, testing, documentation, and dashboard design consistency. Product management of the reporting portfolio Own the BI product roadmap across corporate functions and venue operations; make the trade-off calls when demand exceeds capacity. Ensure each business area — Finance, Operations, Marketing, F&B, Guest Experience — has a clear product owner relationship and a visible backlog.<
The Best Players Need the Best People. This position is responsible for developing platforms and technology solutions across the Golf Technologies department portfolio — including our competitions platforms, statistics platforms, and data delivery platforms. Working with internal and external partners, the incumbent will design and ship complex features and services, owning multi-month projects with real ambiguity. The Senior Software Engineer is a senior technical team member with a strong delivery focus. This role translates fuzzy product or operational needs into clear technical plans, contributes deeply on delivered technical solutions, and weighs reliability, cost, security, and delivery speed. The role works with AI tools and technologies on a day-to-day basis to accelerate delivery and build smarter solutions — from AI-assisted development to incorporating AI/ML capabilities into our platforms. The Senior Software Engineer contributes to technical decisions in design reviews, ensures work items are developed against current standards and best practices, and ensures our applications are future-proofed for further features. The role provides technical support to the Director Software Engineering and VP of Engineering. QUALIFICATIONS Bachelor’s degree in inf
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