Engineering Standards Manager in United States

About the Team The Applied AI Engineering team is responsible for helping customers turn frontier AI capabilities into real products, workflows, and business impact. We act as trusted technical partners across solution design, architecture, implementation, evaluation, and adoption, working alongside customers to build and scale effective AI applications with OpenAI’s technologies. The Codex Applied AI Engineering team focuses on helping organizations transform how software is built with AI. We partner directly with engineering teams and technical leaders to integrate Codex into their software development lifecycle — from identifying high-impact use cases and designing AI-enabled workflows to implementation, evaluation, and scaled adoption. Our work helps ensure AI-powered software development is effective, reliable, secure, and deeply integrated into how engineering organizations operate. About the Role We are seeking an experienced technical leader to join as Manager, Applied AI Engineering (Codex) , leading a team of Applied AI Engineers responsible for driving successful Codex adoption across strategic customers. Your team will work hands-on with customer engineering organizations to design and build AI-enabled development workflows, solve complex implementation challenges, and establish scalable patterns for AI-powered software development. As a manager, you will shape how these technical engagements operate at scale — setting strategy, coaching engineers, determining where the team can have the greatest impact, and ensuring consistently strong execution across customers. You will serve as both a people leader and senior technical advisor, partnering closely with Sales, Product, Research, and Engineering to translate customer needs and real-world usage into better technical approaches, reusable patterns, and product insights. Success in this role will be measured by meaningful and sustained Codex adoption, successful customer outcomes, and the creation of repeat

As a Senior Software Engineer on Coder’s Agentic Engineering team, you’ll build and evolve the systems behind our agentic development experience. You’ll work across the agent harness, integrations, and workflows that connect agents with real development environments. You’ll stay hands-on, solve complex technical problems, and work closely with Product, Design, and other engineers to ship reliable agentic experiences. To provide substantive overlap with the team, this position must be in Eastern Time. What you’ll do here Design and build production systems in Go, with work across React and TypeScript where needed. Improve agent execution, tool use, context management, streaming, and long-running workflows. Extend our provider-agnostic architecture as models and capabilities change. Build reliable integrations between agents, workspaces, tools, and developer infrastructure. Own projects from implementation through rollout and iteration. Contribute to design reviews, code reviews, and technical discussions. Partner with Product and Design to turn agent capabilities into useful developer experiences. Improve the reliability, performance, and operability of agentic systems. What we’re looking for Strong experience building and operating production software systems. Hands-on experience with Go. Experience with React and TypeScript. Experience building systems around LLMs or agentic workflows. Familiarity with model APIs, tool calling, context management, or agent loops. Good understanding of distributed systems and production reliability. Working knowledge of AWS. Strong problem-solving skills and comfort working through technical ambiguity. Someone who contributes beyond their own code through reviews, collaboration, and knowledge sharing. Bonus tacos if you have Experience building coding agents, developer tools, or cloud development environments. Experience with MCP, agent tools, or multi-agent systems. Experience with remote execution, sandboxing, or isolated compute.

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. The Thin Films Equipment Engineering team at Micron develops and enhances advanced semiconductor manufacturing equipment in a fast-paced research and development environment. The team works closely with Process Engineering, Facilities Engineering, and equipment suppliers to enable next-generation memory technologies and achieve world-class equipment performance. Through innovation, collaboration, and data-driven decision-making, the team plays a critical role in advancing semiconductor technology development. As a Thin Films Equipment Engineering Intern, you will gain hands-on experience working with groundbreaking semiconductor equipment and processes. You will support engineering projects focused on equipment optimization, data analysis, and technology development while collaborating with multi-functional teams. This role provides exposure to semiconductor manufacturing, experimental design, and the application of advanced analytics to solve complex engineering challenges. Responsibilities Collect, analyze, and interpret equipment and process data to find opportunities for performance optimization and continuous improvement. Support structured engineering experiments, document findings, and communicate results through technical reports and presentations. Collaborate with Equipment Engineering, Process Engineering, Facilities Engineering, and equipment suppliers to address technology-development challenges and improve equipment performance. Develop an understanding of equipment hardware,

Senior Product Review Engineer (Liaison Engineering) — USA - Travis AFB, CA. Apply via Workday.

Senior Level Product Review Engineer (Liaison Engineering) — USA - McConnell AFB, KS. Apply via Workday.

Senior Product Review Engineer (Liaison Engineering) — USA - McGuire AFB, NJ. 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. 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 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 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 GTM Growth Engineering builds AI-native products and systems that help OpenAI's go-to-market and B2B marketing organizations operate with greater speed, focus, and leverage. Our mandate is revenue leverage: products tied directly to pipeline quality, customer engagement, seller and marketer productivity, and the speed at which OpenAI can bring its technology to customers. We build the infrastructure and user experiences behind high-impact GTM workflows, including customer context, prioritization, routing, campaign execution, review surfaces, feedback loops, and measurement. Our work combines product craft, applied AI, reliable systems, and thoughtful operational design. About the Role We’re looking for a product-minded Software Engineer to build AI-powered products and full-stack experiences for GTM Growth Engineering. You will own meaningful product slices end to end, from user experience and frontend implementation to backend APIs, integrations, data models, instrumentation, and launch readiness. This is a role for engineers who want to build products that do real work in production. You will partner with Product, Design, Data Science, Sales, B2B Marketing, and operations teams to understand high-value workflows and ship systems that improve customer engagement, pipeline, conversion, and team productivity. The role is ideal for a strong product engineer who can move between product craft, systems engineering, applied AI, and measurable business outcomes. You should be excited to build from ambiguous problem statements, ship quickly, and improve products based on real user feedback. What You'll Do Build AI-powered products and workflows that help sales and B2B marketing teams identify opportunities, coordinate work, and engage customers more effectively. Own full-stack product experiences from prototype through launch, instrumentation, iteration, and production hardening. Design intuitive user journeys that combine polished interfaces, reliable servi

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 Manager, Software Engineering About the Role This is an exciting opportunity to join Mastercard's global credit card authorization program. We facilitate billions of transactions among issuers, acquirers, and service providers worldwide. We are looking for a strong software engineering people leader to build advanced technologies and applications that revolutionize payments. As a Software Engineering Manager, you will lead a cross-functional team while helping shape the strategic direction of critical payment systems. You will be responsible for driving engineering excellence across software design, development, testing, security, performance, operability, and delivery, ensuring solutions are scalable, resilient, and aligned with Mastercard's enterprise objectives. Role As a Software Engineering People Manager, you will: Team Leadership & Development • Serve as a servant leader for a cross-functional engineering team including Software Engineers, Technical Program Managers, and Product Manager-Technical roles. • Recruit, develop, and retain top engineering talent, ensuring a high-performing and diverse team. • Coach and mentor engineers, helping them grow technical expertise, leadership capabilities, and business acumen. • Conduct performance reviews, career dev

We’re here for one reason and one reason only – to cure cancer. Every moment is dedicated to developing treatments and every action moves us one step closer to our goal. We’ve made incredible scientific breakthroughs and our pioneering personalized CAR T-cell therapies have changed the paradigm. But we're not finished yet. Join Kite, as we make even bigger advances in cancer therapies, and help shape where our business and medical science goes next. We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Kite and help create more tomorrows. Job Description Position Summary The Senior IT Quality Engineering Specialist serves as the technical lead for the Kite Laboratory Information Management System (KLIMS) within North America West Coast (El Segundo). This role is responsible for the operational stability, compliance, maintenance, enhancement, and technical governance of the LabVantage platform and associated integrations. The position partners closely with Quality Control, Manufacturing, Validation, Infrastructure, and Kite Business stakeholders to ensure reliable and compliant laboratory operations. Key Responsibilities System Administration & Operational Support • Provide day-to-day administration and technical support for KLIMS and related

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. CVS Health is seeking an SDET Manager to lead Quality Engineering and software delivery transformation across the Medicare Sales & Acquisition ecosystem. This role is critical to modernizing how we build, test, and deliver software, including embedding AI-driven capabilities into the SDLC. You will translate business workflows (Sales, Enrollment, Broker, and Telesales) into scalable, automated testing solutions that improve speed, quality, and operational efficiency. This is a hands-on technical leadership role responsible for driving test automation strategy, enabling intelligent SDLC pipelines, and building a high-performing engineering team aligned to enterprise goals. This role will also help shape the team's transition toward AWS-native test infrastructure and agent-orchestrated cycles, positioning the organization to scale automation alongside delivery volume in future years. Key Responsibilities Lead the design and implementation of AI-augmented Quality Engineering solutions — including agentic test generation, self-healing frameworks, and AI-assisted defect analysis — advancing the SDLC toward an AI-driven Automated Delivery Lifecycle (ADLC) Drive the migration of automation frameworks and test data management onto AWS-native services (e.g., Bedrock for model orchestration, Lambda/Step Functions for event-driven test pipelines), enabling

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. CVS Health is seeking an SDET Manager to lead Quality Engineering and software delivery transformation across the Medicare Sales & Acquisition ecosystem. This role is critical to modernizing how we build, test, and deliver software, including embedding AI-driven capabilities into the SDLC. You will translate business workflows (Sales, Enrollment, Broker, and Telesales) into scalable, automated testing solutions that improve speed, quality, and operational efficiency. This is a hands-on technical leadership role responsible for driving test automation strategy, enabling intelligent SDLC pipelines, and building a high-performing engineering team aligned to enterprise goals. This role will also help shape the team's transition toward AWS-native test infrastructure and agent-orchestrated cycles, positioning the organization to scale automation alongside delivery volume in future years. Key Responsibilities Lead the design and implementation of AI-augmented Quality Engineering solutions — including agentic test generation, self-healing frameworks, and AI-assisted defect analysis — advancing the SDLC toward an AI-driven Automated Delivery Lifecycle (ADLC) Drive the migration of automation frameworks and test data management onto AWS-native services (e.g., Bedrock for model orchestration, Lambda/Step Functions for event-driven test pipelines), enabling