Engineering Specialist in United States

About the team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is based in San Francisco. W

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 Engineering Program Manager, you will help turn complex infrastructure strategy into executable programs across electrical, mechanical, controls, network, hardware, construction, commissioning, deployment, and operations workstreams. You will partner with research, hardware engineering, data center engineering, site development, supply chain, security, EHS, finance, legal, operations, and external delivery partners to bring OpenAI's infrastructure vision to life. About the Role We are looking for an Engineering Program Manager (EPM) to lead assigned infrastructure programs focused on production and non-production network integration, controls coordination, and the design and deployment of data hall or whitespace facilities. The EPM will support functional Directly Responsible Individuals (DRIs) across network, controls, structural, electrical, and mechanical disciplines. Key responsibilities include coordinating assigned workstreams and program controls, maintaining risks and interfaces, and supporting readiness within the network and data hall deployment track. The ideal candidate thrives on bringing structure to complex environments characterized by ambiguous technical requirements, large partner ecosystems, tight deadlines, and high operational stakes. This individual must be adept at keeping teams aligned on decisions, risks, dependencies, schedules, and readiness criteria, and escalating gaps or decision points when needed. Candidates should have a proven track record of managing technically challenging engineering programs across major lifecycle phases, including design, validation, procurement, construction, c

About the team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is based in NYC. We use a hy

Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, faster. The company is headquartered in San Francisco and has offices in Boston, New York, Austin, Tokyo, London, and Bangalore - where Postman was founded. Postman is privately held, with funding from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. Learn more at postman.com or connect with Postman on X via @getpostman. P.S: We highly recommend reading The "API-First World" graphic novel to understand the bigger picture and our vision at Postman. The Opportunity As the Head of AI Platform Engineering at Postman, you will lead the alignment of AI development with our growing API platform. You will drive the AI roadmap with a focus on expanding AI-driven API collaboration and agentic capabilities across the platform. This role requires a leader who can identify market opportunities, coordinate cross-functional AI initiatives, and foster strong partnerships to amplify the Postman AI platform's impact What You’ll Do Lead the development and execution of Postman’s AI platform strategy, focused on API ecosystem growth and platform innovation. Drive the AI roadmap, concentrating on API integration, platform expansion, and AI-driven agent functionality. Identify and capitalize on market opportunities for AI-enhanced API collaboration and intelligent agent features. Collaborate closely with business units, product teams, engineering, and external partners to ensure alignment and successful AI initiatives deployment. Oversee implementation with core AI platforms (OpenAI, Anthropic, AWS, etc)), ensuring technical and strategic alignment with AI features and API lifecycle improvements.

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. Snowflake is seeking a Senior People Partner to support our Engineering organization as a strategic advisor to Engineering leadership and their teams. This is a unique opportunity to partner at the heart of innovation—helping shape how world-class engineering teams scale, evolve, and deliver in a rapidly changing technology landscape. We are looking for a People Partner who is deeply curious, energized by complexity, and excited about the transformative impact of AI on both the business and Snowflakes around the world. You bring a strong point of view, a bias for action, and a genuine enthusiasm for building alongside leaders who are defining the future of data and AI. This role is based in either our Bellevue, WA or Menlo Park, CA office, with in-office attendance required three days per week. The Senior People Partner will partner closely with Engineering leadership, the broader People Partner team, and People Centers of Excellence (COEs) to shape and execute a people strategy that enables innovation, scale, and organizational effectiveness. THE IMPACT YOU WILL MAKE Serve as a trusted advisor to Engineering leadership, providing candid, data-driven counsel on organizational, talent, and leadership decisions. Translate business priorities into a clear, integrated people st

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 Vice President, Software Engineering Role Overview Mastercard is seeking a Vice President of Engineering to lead the Developer Workbench, a strategic platform designed to deliver a unified, AI-enabled, end-to-end software engineering experience across the enterprise. The Developer Workbench will bring together core engineering products, developer tools, AI-assisted coding capabilities, development environments, testing workflows, deployment pipelines, cloud development experiences, and developer insights into one cohesive platform. This leader will be accountable for transforming the Workbench from a set of disconnected tools and services into a productized developer experience that improves productivity, accelerates onboarding, increases adoption of modern engineering capabilities, and strengthens governance across the software development lifecycle. This is a senior engineering leadership role for a builder, integrator, and enterprise change leader who can operate across product, engineering, architecture, security, finance, learning, and senior technology leadership. ________________________________________ Key Responsibilities Lead the Developer Workbench Engineering Strategy • Define and execute the engineering strategy for the Developer Workbench. • Establish the technical architectu

Work Flexibility: Onsite As the Manager, Quality Assurance , you will lead quality assurance activities that support product quality, process performance, audit readiness, and continuous improvement across site operations. Working closely with Operations, Global Quality, Regulatory Affairs, and supplier partners, you will help ensure quality systems remain effective, compliant, and aligned with business objectives. This role is Onsite in Mahwah, New Jersey . What You Will Do Lead the Quality Assurance team, providing technical guidance and quality oversight across manufacturing and operations, supports functions to drive continuous improvement and compliance. Partner with site leadership to ensure products consistently meet customer expectations, regulatory requirements, and applicable quality standards. Develop, coach, and retain a high-performing team while fostering a culture of inclusion, accountability, collaboration, and employee engagement. Drive quality system compliance by partnering with functional leaders to establish, communicate, and maintain quality standards, requirements, and responsibilities. Lead site readiness activities and support internal, corporate, notified body, FDA, and other regulatory audits and inspections. Oversee the management of nonconforming products, product and process deviations, risk assessments, corrective actions, and preventive actions to ensure effective resolution and compliance. Monitor and improve Quality performance indicators, including NCR, CAPA, compliance, and operational quality metrics, and implement corrective actions for adverse trends. Support the development and execution of local and global Quality Operations strategies that improve product quality, operational efficiency, risk management, and regulatory compliance. <

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. Position Summary Designs, develops, and implements AI solutions and systems by applying advanced technical expertise to architect and code software applications, conduct system testing and debugging, collaborate with cross-functional teams, and contribute to the overall technical direction and innovation of AI engineering projects. Required Qualifications 5-7 years of professional experience in software engineering and application development. 2&#43; years of hands-on experience on LLMs & Generative AI (LLM) techniques. Expert proficiency in programming skills especially Python, Google Cloud platform and system architecture. Experience in leading engineering teams and driving technical roadmaps. Preferred Qualifications Define and implement AI safety frameworks Strong problem-solving skills and the ability to think strategically. Excellent communication skills for effective collaboration. Cross-functional collaboration Education Bachelor's degree or equivalent work experience in Mathematics, Statistics, Computer Science, Analytics, Engineering, or related discipline. Master's degree preferred <p style="text-align:in

About the Team The Applied AI Engineering team partners closely with customers to help them move from experimentation to production with OpenAI’s technologies. We act as trusted technical advisors, working across customer strategy, architecture, deployment, and adoption to help organizations realize meaningful impact from frontier AI. The Startups segment serves fast-moving, high-growth companies that are often building new products, workflows, and businesses directly on top of AI. These customers move quickly, operate with high ambiguity, and expect practical, creative, and technically rigorous partnership. About the Role We are looking for an Applied AI Engineering Manager, Startups to lead and scale the Startups Applied AI Engineering motion. This team helps high-growth startups move quickly from experimentation to production, unlock meaningful usage, and build durable technical partnerships with OpenAI. This leader will operate in a high-velocity customer segment where founders, CTOs, and technical teams expect speed, judgment, and hands-on problem-solving. They will balance team leadership, technical depth, customer prioritization, and cross-functional influence across Sales, Product, Engineering, Research, and broader go-to-market teams. In this role, you will define how OpenAI supports startup customers at scale: identifying where deep technical engagement can unlock outsized impact, building repeatable deployment mechanisms, and ensuring the team can serve a broad and dynamic customer base without losing quality or strategic focus. In this role, you will: Craft and continuously refine the strategic vision and operating model for the Startups Applied AI Engineering team, aligning it with OpenAI’s broader company objectives and the evolving needs of high-growth startup customers. Lead, mentor, and grow a team of high-performing technical ICs supporting startup customers across AI-native, developer-led, and product-led companies. Help startups move from early e

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,

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. Plaid's Infrastructure team builds the platforms and tooling that help engineering teams develop, deploy, and operate production systems safely. Release Engineering owns the path from merge to production, including Plaid's zero-touch deployment system, progressive rollouts, metric-gated analysis, and automatic rollback. Our goal is to make safe shipping the default for every product team. As a Staff Site Reliability Engineer on Release Engineering, you'll define and scale Plaid's reliability practices across product engineering. You'll architect our SLO and error-budget programs, drive the adoption of progressive delivery, and ensure new products are production-ready. By partnering across product and platform teams, you'll translate complex production needs into intuitive, self-service tooling. This is a hands-on technical leadership role where you'll shape the future of our deployment systems—ensuring they remain fast and safe even as AI-assisted development increases code velocity. What excites you Lead the expansion of reliability standards across product engineering, converting foundational infrastructure into lasting operational habits and tooling. Architect and manage the SLO and error-budget

We're looking for an Engineering Manager II to own and grow the Observability Pipelines engineering org at a pivotal moment in the product's lifecycle. Observability Pipelines is Datadog's on-premise, vendor-agnostic telemetry pipeline product, with a lot still to build as it grows and scales. It sits at the center of a fast-consolidating market, is central to Datadog's data pipeline optimization story for Logs and Metrics customers. This is a build-and-scale opportunity: you'll grow the management and technical leadership layers, co-own the roadmap with Product, and define how this org operates as it continues to expand. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You'll Do: Directly manage the OP org including EM1s across NYC and Paris, set technical direction, and be the connective tissue across a distributed team Build out the management and technical leadership layers as the org continues to grow - today ~20 ICs Partner directly with Product to co-own the roadmap and strategy, helping decide where OP’s engineering investment goes next Set and evolve the operating rhythm across the group: planning cadence, on-call and incident standards, and cross-team alignment Own key cross-org relationships with the SaaS Logs Pipelines team, the BYOC team, and the Vector open-source community Coach managers and senior engineers, and build the succession and growth plans that let the org scale beyond you Who You Are: Experienced managing managers across distributed teams, with a track record of raising the bar on how those teams operate, not just delivering through them Back

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