Lead Full Stack Software Engineer Application Development Jobs

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 NYC. 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 compar

About the team The OpenAI for Government team is a dynamic, mission-driven group leveraging frontier AI to transform how governments achieve their missions. Our team works to empower public servants with secure, compliant AI tools (e.g., ChatGPT Enterprise, ChatGPT Gov) and mission-aligned deployments that meet government technical requirements with strong reliability and safety. About the role Forward Deployed Engineers (FDEs) lead complex deployments of frontier models in production. You will embed with our most strategic government and public sector customers—where model performance matters, delivery is urgent, and ambiguity is the default. You’ll map their problems, structure delivery, and ship fast. This includes scoping, sequencing, and building full-stack solutions that create measurable value, while driving clarity across internal and external teams. You will work directly with defense, intelligence, and federal stakeholders as their technical thought partner, guiding adoption, maximizing mission impact, and ensuring successful deployments at scale. Along the way, you’ll identify reusable patterns, codify best practices, and share field signal that influences OpenAI’s roadmap. This role is based in Washington DC, Seattle or 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, including on-site work with customers. In this role you will Own technical delivery across multiple government deployments, from first prototype to stable production. Deeply embed with public sector customers to design and build novel applications powered by OpenAI models. Enable successful deployments across customer environments by delivering observable systems spanning infrastructure through applications. Prototype and build full-stack systems using Python, JavaScript, or comparable stacks that deliver real mission impact. Proactively guide customers on maximizing business and operational value from

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 Tokyo. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. Travel is expected in this role, mainly within Japan. To succeed in this position you must be bilingual—fluent in both Japanese and English (spoken and written). Please note that your resume must be submitted in English, and the interview process will include conversations in both languages. 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 Bri

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 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 Sydney. 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, JavaScr

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 Singapore. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. 50% travel is expected. 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 P

About the Role: The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding and ads optimization that shape the future of streaming. We are seeking a highly skilled Staff Machine Learning Engineer to contribute to transformative projects in video personalization. In this role, you will design and implement advanced algorithms and systems to improve our personalization strategy. As a senior technical expert, you will tackle complex problems in machine learning at scale, collaborating closely with cross-functional teams to develop and optimize machine learning-driven solutions. This is a hybrid role in our Toronto office. What You'll Do: Lead the design, development, and implementation of advanced recommendation systems and algorithms for a global audience Conduct deep dives into algorithmic components and systems, ensuring that models are optimized for both performance and scalability across multiple regions and product areas Build and deploy high-impact robust ML pipelines, including data extraction, feature development, model training, testing, and deployment Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring they meet business goals and provide high-quality user experiences. Work closely with Product, Engineering, and Data Science teams to align on product requirements, set expectations, and deliver machine learning-driven solutions that improve user engagement Your Background: 8+ years of industry experience building production Machine Learning systems MSc or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related field Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks Proficiency in building and deploying full-stack machine le

About the Role The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding, and ads optimization that shape the future of streaming. We are seeking a VP / Director of Machine Learning Engineering to lead and build a high-performing team while staying close to the technical work. This is a hands-on leadership role: you will set the strategic direction for our recommendation, personalization, and ads optimization systems, including recommendation foundation modeling, and you will stay in the algorithms and the code, conducting deep dives into modeling components and guiding the hardest technical decisions yourself. You will tackle complex machine learning problems at scale and partner closely with cross-functional teams to ship solutions that measurably improve how hundreds of millions of viewers experience Tubi. What You’ll Do Lead, build, and grow a high-performing ML engineering team, fostering a culture of technical excellence, ownership, and rapid iteration. Define and drive the ML strategy and long-term technical roadmap for recommendation, personalization, and ads optimization, including recommendation foundation modeling, identifying opportunities for ML to shape Tubi’s broader product and business strategy. Stay hands-on: conduct deep dives into algorithmic components and systems, ensuring models are optimized for both performance and scalability across regions and product areas. Lead the design, development, and implementation of advanced recommendation systems and algorithms, contributing directly to the most challenging technical problems. Build and deploy robust, full-stack ML pipelines: data extraction, feature development, model training, testing, deployment, and serving. Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring

About Scale AI Scale's rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing governments around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for national LLMs Upskilling and advisory services to spread the impact of AI As these applications move from prototype to production, we're investing heavily in the infrastructure and people that keep them reliable, secure, and trusted by our government partners. At Scale, we're not just building AI solutions - we're enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you're ready to shape the future of AI in the public sector and be a founding member of our team, we'd love to hear from you. Role Overview We are looking for a technically strong and customer-oriented Engineering Manager to lead the development of AI applications for Saudi government clients. This role sits at the intersection of engineering leadership, AI/ML delivery, and direct client engagement—requiring someone who is equally comfortable presenting to a government stakeholder as they are reviewing a system architecture or shipping code. As a founding member of our regional team, you will help define how Scale AI shows up for some of the most ambitious public sector AI initiatives in the Gulf. If you thrive in fast-paced, high-impact environments and want to shape the future of AI in government, we would love to hear from you. What You'll Do Lead and manage a team of engineers delivering AI-powered applications for KSA government clients, ensuring high-quality output and on-time delivery Serve as the primary technical point of contact for KSA government stakeholders—translating complex engineering concepts into clear, accessible language for non-technical audiences Design, build, and optimize full stack AI applications end-to-end, fro

About the Role As a member of the Data team within the Go-to-Market organization, you will help build a data-driven culture, improve decision-making, and advance strategic initiatives through analytics. This is a full-stack data role spanning data modeling, metric definition, visualization, analysis, and self-service tooling. You will build trusted, scalable data sources and products that give the business reliable, actionable insights. The work calls for judgment: you will choose the tool, approach, and level of investment that best fit each problem, from a focused analysis to a durable production data product. As a core partner to the GTM organization, you will address both foundational and ad hoc analytics needs. You will turn complex data into clear narratives that help technical and non-technical audiences understand what is happening, why it matters, and what they should do next. In This Role, You Will Partner closely with GTM teams to proactively identify high-impact questions and translate business needs into data models, metrics, analyses, and scalable technical solutions. Define, source, validate, and operationalize the metrics that guide the business, helping teams incorporate them into planning and day-to-day decisions. Lead cross-functional data projects across established and emerging business areas, including setting the data strategy for greenfield domains. Build scalable data models and pipelines that integrate and transform data from multiple sources into trusted, accessible datasets. Create dashboards, reports, analytical tools, and other data products that enable stakeholders to answer questions independently. Own the lifecycle of metrics, analytical models, and data products from initial exploration and prototyping through production and ongoing maintenance. Choose the most effective approach for each problem—whether an analysis, metric, data model, visualization, or self-service product—based on the audience, urgency, complexity, and expected v

About the Team OpenAI's Enterprise team builds AI-powered enterprise products and shared platform capabilities that help organizations put advanced AI to work securely and at scale. Our work spans enterprise workflows, agent experiences, integrations, identity, administration, security, governance, and deployment. About the Role As a Technical Program Manager on Enterprise, you will lead the technical strategy and execution behind the products and shared capabilities that make ChatGPT, Codex, and future OpenAI products useful, secure, and scalable for organizations. You will translate customer needs, competitive dynamics, and product priorities into actionable plans, influence architectural direction, and deliver durable capabilities across application, platform, and infrastructure layers. The role requires deep technical fluency, strong product judgment, and the ability to move between hands-on execution and broader enterprise strategy. 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: Drive technical strategy and execution for enterprise product and AI workflow initiatives, from design through implementation, launch, customer rollout, and iteration. Partner with engineering teams to influence architectural direction, interface definitions, and implementation tradeoffs across full-stack products, APIs, integrations, and shared platform systems. Translate enterprise customer requirements into actionable product priorities across AI-powered workflows, agent experiences, integrations, permissions, data access, evaluations, identity, security, governance, and deployment readiness. Represent the needs of enterprise buyers, IT administrators, security teams, business leaders, developers, and end users in product and technical decisions. Identify adoption barriers, competitive gaps, and opportunities to make OpenAI products easier for organizations

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: As Engineering Manager for our verticals application team, you'll lead a team of engineers building full-stack applications, backend and frontend, that bring AI into critical sectors, starting with the Pharmaceutical industry and expanding into areas like finance and healthcare over time. You'll own the application and user-experience layer, partnering closely with the ML engineering teams who build the underlying data and agent infrastructure. Day to day, that means working with product managers, designers, and ML engineers to ship best-in-class applications, while hiring, mentoring, and growing your team. We're looking for someone who has built AI-first products deeply integrated with agentic systems, and who can deliver secure systems that users can trust in high-stakes environments. Our pace is startup-fast, but the bar is enterprise-high: these applications must be reliable, observable, safe, and auditable from day one. Key Responsibilities: Lead and manage backend and frontend engineers, fostering collaboration and ensuring predictable delivery Act as the primary interface between Product and Engineering tea

About the Role Join Peloton’s Global Network Services team as a Senior Engineer, sitting at the unique intersection of high-scale enterprise networking and high-stakes media production. In this role, you will architect and support the global infrastructure that powers our corporate offices, warehouses, and flagship New York Broadcast Studio. Acting as the key bridge between Global Cloud Engineering and Studio Operations, you will deploy highly resilient, scalable architectures that deliver live streaming content seamlessly to millions of members worldwide. Your Daily Impact Global Architecture & Deployment: Design, optimize, and secure Peloton's global network footprint, integrating Cisco, Meraki, Aruba, and Palo Alto Networks across hybrid on-premises and AWS environments. Studio & Broadcast Reliability: Lead deep-dive traffic analysis and troubleshooting for our NY studio, ensuring 24/7 uptime for live broadcasts, real-time video streaming, and OTT media delivery. Operational Leadership & Lifecycle Management: Manage the end-to-end network project lifecycle—from traffic shaping and SD-WAN optimization to establishing SOPs, security policies (with InfoSec), and handling Tier-3 disaster recovery. You Bring To Peloton Broad & Deep Network Expertise: 8+ years in Network Engineering, including 6+ years in complex SaaS environments and 4+ years designing public cloud networking (specifically AWS). Advanced Protocol & Security Mastery: Expert knowledge of L2/L3 protocols (BGP, OSPF, EIGRP), security protocols (IPsec, 802.1x, RADIUS), SD-WAN, and SDN/SDDC full-stack solutions. Media & Streaming Specialization: 3+ years optimizing IP networks specifically for live video delivery, utilizing multicast/unicast technologies and streaming protocols like HLS, RTMP, and SRT. Education & Elite Certifications: A Bachelor’s degree in Engineering or Computer Science, backed by active CCIE or JNCIE certifications (required). Collaborative Mindset: A curious

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . As an Engineering Manager on the FINT (Financial Intelligence) team within FinHub in the Platform group, you'll lead the engineers building the account and transaction history infrastructure that underpins every Coinbase product. FINT owns the universal account primitive, the real-time transaction history engine, and the internal developer experience platform for FinHub. You'll guide your team through a critical inflection point: re-architecting these foundational systems for the next decade of scale while enabling new financial products like sub-accounts, retirement accounts, and agentic trading experiences. What you'll do: Lead and grow a team of 6 engineers across multiple levels, coaching on technical excellence, career development, and organizational impact Drive the re-architecture of core account and history systems to support new product primitives and higher throughput demands at Coinbase's next stage of growth Own the Finhub Tools roadmap, building internal UIs, dashboards, and agentic workflows that accelerate engineering and operations teams across the company Shape architectural decisions across distributed systems, streaming pipelines, and full-stack tooling, fostering a culture of high-quality code and thorough design reviews Collaborate with product, finance, and engineering leadership to define and execute a quarterly roadmap, breaking complex infras