Lead Engineer 4 Ui Full Stack Developer Manager Manager in Singapore

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The community you will join: As a Staff Experience Designer supporting international expansion initiatives, you will partner with cross-regional partners (country managers, localization experts, researchers, product specialists, engineers, data scientists, etc.) to craft beautiful, usable, forward-looking products that empower people. Our design charter is to help foster an emotional connection with our community, keeping usability and accessibility as our prime virtues. We do our best to practice inclusive design at every turn, spanning across online and offline experiences we create for our Host and Guest communities. The difference you will make: As a Staff Experience Designer, you will play a critical role in shaping how Airbnb shows up in markets across APAC and globally. You will help ensure our global products feel truly local—adapting core experiences to regional needs while feeding market insights back into the broader product strategy. Sitting at the intersection of product, design, and regional strategy, you will work across time zones and functions to define and deliver an international roadmap that spans both tactical UI improvements and larger strategic bets. You will bring a high bar for visual and interaction design craft, model AI-enabled ways of working, and provide design leadership in a space that is growing in complexity and impact for Airbnb globally. The Staff Experience Designer is an individual contributor (IC) role that will report to a Manager or Director of Experience Design. A typical day: Lead the design of multiple international initiati

Lead Staff Engineer / Lead Principal Engineer PD SG Diffusion/Implant — Fab 10N/X, Singapore. Apply via Workday.

SNR/STAFF SHIFT ENGINEER LEAD, TD MFG DEV ENGG — Fab 10N/X, Singapore. Apply via Workday.

Dry Etch Principal Engineer/ MTS Lead, Process Development, Advance NAND — Fab 10N/X, Singapore. Apply via Workday.

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

Staff Engineer, Product Integration Lead, HIG High Bandwidth Memory — Fab 10A, Singapore. Apply via Workday.

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 . Software Engineer, Data Layer As a Software Engineer on the Data Layer team within the Platform group, you'll shape the API (GraphQL) platform that connects every client application to Coinbase's backend services, handling the majority of user traffic across Consumer, Base, and Institutional products. You'll own the critical systems that route and serve API requests at scale, improving reliability, performance, and developer experience for hundreds of engineers building on this foundation layer. What you'll do: Own and deliver projects end to end, from scoping and system design through implementation, rollout, and production validation, driving measurable progress on the team's highest-priority initiatives. Design and build high-reliability, low-latency systems serving millions of users, tackling challenges like caching, upstream service optimization, and efficient connection management at scale. Build and improve the API framework and tooling that hundreds of engineers depend on, making it fast and easy for teams across the company to build, test, and ship independently. Drive operational excellence across T0 services: own SLOs, improve observability, lead incident response, and reduce operational toil so the team can invest in high-leverage work. Partner cross-functionally with product engineering teams to design API schemas, support service launches, and ens

As an Enterprise Sales Engineer, you'll partner with Sales to help customers understand the value of Datadog and how it solves their most important technical and business challenges. You'll lead technical evaluations, deliver compelling demos, and guide customers through the journey from discovery to successful adoption. You'll act as a trusted advisor, bridging business goals with technical solutions, and play a key role in winning new business and expanding existing accounts. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Own the sales process in partnership with Account Executives by leading and shaping the technical strategy across opportunities from PG to Closed Won Lead customer discovery to uncover technical challenges, business goals, and success criteria, then translate those needs into tailored Datadog solutions Deliver engaging product demos, technical presentations, and workshops that connect platform capabilities to customer outcomes Project manage technical evaluations (POVs) end-to-end: scoping use cases and requirements, defining success criteria, building a project plan with clear timelines, and holding all participants accountable to the process Identify and cultivate technical champions within customer accounts, empowering them to advocate for Datadog adoption and drive consensus internally Participat e actively in structured product and engineering field feedback sessions, serving as the technical voice of the customer to help shape product direction Maintain operational excellence by ensuring activity, deal progress, and customer interactions are accurately documented and up to date in related systems Collaborate cross-functionally with Product, Support, and GTM teams to address customer needs and resolve technical bloc

As an Enterprise Sales Engineer, you'll partner with Sales to help customers understand the value of Datadog and how it solves their most important technical and business challenges. You'll lead technical evaluations, deliver compelling demos, and guide customers through the journey from discovery to successful adoption. You'll act as a trusted advisor, bridging business goals with technical solutions, and play a key role in winning new business and expanding existing accounts. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Own the sales process in partnership with Account Executives by leading and shaping the technical strategy across opportunities from PG to Closed Won Lead customer discovery to uncover technical challenges, business goals, and success criteria, then translate those needs into tailored Datadog solutions Deliver engaging product demos, technical presentations, and workshops that connect platform capabilities to customer outcomes Project manage technical evaluations (POVs) end-to-end: scoping use cases and requirements, defining success criteria, building a project plan with clear timelines, and holding all participants accountable to the process Identify and cultivate technical champions within customer accounts, empowering them to advocate for Datadog adoption and drive consensus internally Participat e actively in structured product and engineering field feedback sessions, serving as the technical voice of the customer to help shape product direction Maintain operational excellence by ensuring activity, deal progress, and customer interactions are accurately documented and up to date in related systems Collaborate cross-functionally with Product, Support, and GTM teams to address customer needs and resolve

About the Team The Applied AI Engineering team is responsible for helping developers and enterprises safely and effectively deploy OpenAI technologies in production. We act as trusted technical advisors and thought partners for customers, working side by side with their teams to identify high-value use cases, design practical architectures, and move from prototype to durable deployment. Cybersecurity is one of the most urgent domains where AI can help. Security teams are under pressure to reason across code, logs, infrastructure, tickets, alerts, and vulnerability data faster than ever. As frontier models become more capable, organizations need deep technical guidance on how to evaluate, validate, and safely deploy AI systems in security-critical workflows. About the Role We are looking for an Applied AI Engineer, Cyber to partner with customers and help them apply OpenAI models, APIs, Codex, and agentic workflows to real cybersecurity use cases. You will work with CISOs, security executives, application security leaders, SOC teams, security engineering teams, and hands-on practitioners to identify where AI can create measurable security outcomes. This is a customer-facing technical role for someone who can move fluidly between executive strategy, practitioner-level cyber depth, and hands-on solution design. You will help customers evaluate and deploy workflows such as secure code review, vulnerability triage, threat modeling, remediation, SOC and incident response workflows, detection engineering, cloud security, GRC automation, and security validation. You will collaborate closely with Sales, Solutions Engineering, Product, Engineering, Research, and Security to turn customer needs into safe deployment patterns, reusable field assets, and product feedback. This role is based in our Singapore office. We offer relocation support to new employees. In this role, you will: Deeply embed with strategic customers as the technical lead for AI-enabled cybersecurity workflow

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! About North: North is Cohere's cutting-edge AI workspace platform, designed to revolutionize the way enterprises utilize AI. It offers a secure and customizable environment, allowing companies to deploy AI while maintaining control over sensitive data. North integrates seamlessly with existing workflows, providing a trusted platform that connects AI agents with workplace tools and applications. Why This Role? This role offers a unique opportunity to shape how enterprises harness the power of AI in real-world applications. As a bridge between our core North product and our clients’ engineering teams, you’ll be at the forefront of solving complex problems and securely integrating AI into critical sectors such as finance, healthcare, and telecommunications. Our esteemed clients include industry leaders like RBC, Dell, and LG CNS. We are seeking engineers who deeply care about customers and want to work at the cutting edge of Agentic AI. Note: between 20 - 40% travel anticipated In this role, you will: Lead end-to-end deployment of North in private cloud and on-premises environments, including planning, configuration, testing, and r

Integration Reliability Engineer, Technical Operations About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team APAC Payins TechOps is a newly formed team based in Singapore. Our charter is to improve the health and resilience of our payment acquiring volume, making it easier for Stripe to build and operate the integrations that support hundreds of billions of dollars in payments annually. Our team partners closely with payments and platform engineering teams to assess systems or processes that create high operational workloads, then develops durable solutions via code, tooling, data, and process improvements. We are responsible for the financial data quality of key systems at Stripe, ensuring that data is quarantined without impacting downstream systems while implementing the right changes upstream to prevent recurring issues. The team's work has a direct impact on Stripe's ability to expand into new markets and offer more sophisticated payment features to merchants. What you’ll do Responsibilities Scope and lead technical initiatives end-to-end: identify problems worth solving, propose the right solution approach, and deliver on that solution — not just execute on a pre-defined plan. Investigate problems in systems by tracing problems through Stripe’s stack. You’ll examine code, write SQL queries, read logs, and inspect data pipelines to understand system behavior, then make changes to address. Examine updates being made by Stripe’s financial partners to understand impact, and make the changes within Strip

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We’re looking for a product manufacturing engineer, who will be responsible for driving technical initiatives related to manufacturing to ensure product success from concept to launch and through mass production with a specific focus on PCB and PCBa manufacturing and process. You’ll have the opportunity to work with a wide range of stakeholders, from design engineering and operations teams,TPMs, external industry vendors and partners to ensure that all products are developed and delivered on time and to the highest quality standards. 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: In this role, you’ll be responsible for driving manufacturing and quality initiatives to ensure product success from concept to launch Lead the product design and the manufacturing process for next-gen AI hardware system development, you will have the opportunity to work with a wide range of stakeholders, from design engineering and operations teams, TPMs and external industry vendors and partners to ensure that all products are developed and delivered on time and to the highest quality standards. Lead the team to establish NPI product manufacturing process, systems and quality controls, defining clear milestones and deliverables, drive internal process improvements across multiple terms and functions Provide hands-on product manufacturing analysis during desi

At Breeze, we're building the AI-powered infrastructure layer for global commerce, making it radically simpler for businesses to sell, get paid, and operate across markets. We go far beyond traditional payment processing. Breeze combines global payments, AI, stablecoins, and a Merchant of Record-like model to take on the complexity businesses typically manage themselves, including compliance, risk, fraud, chargebacks, reconciliation, and customer support. Our goal is simple: let businesses focus on building and selling great products while Breeze handles the complexity behind getting paid. Backed by Sequoia Capital , Multicoin Capital , and The Chainsmokers , Breeze is a successful, rapidly growing, and exceptionally well-capitalized company. We have the runway to think long term while remaining early enough that every person joining today can have a meaningful impact on what we build. We are hiring a Staff Machine Learning Engineer, Risk! As our Staff Machine Learning Engineer, Risk, you'll lead the evolution of our ML platform for payment risk, building the production-grade capabilities behind feature engineering, model training, deployment, monitoring, and continuous improvement. Risk decisions sit at the center of our business, and you'll own how those models get built, shipped, and kept healthy. This role reports to the CTO. You'll work closely with Risk, Software Engineering, and Data Engineering, and you'll be the senior technical voice for ML on the risk team. We're looking for someone who thrives in fast-moving environments, wants meaningful ownership, and is excited to build rather than simply maintain. What You'll Do Design and build ML infrastructure for payment risk detection, using Databricks as the core platform, in close partnership with software and data engineers. Bring structure to the team's ML environment: feature pipelines, versioning, job orchestration, and monitoring. Design and productionize models rather than just prototype them, including

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 This is a founding 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. This is not a management role, however you'll 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 Singapore. We use a hybrid model of 3 days in office and offer relocation assistance. Travel up to 25-50% is required. In this role, you will: Own the technical delivery plan for multiple interdependent workstreams. Translat