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Who We Are 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 The Datalake team builds and maintains Stripe's foundational data access and governance infrastructure — the paved path for safe, fast, and compliant access to Stripe's critical big data assets. We serve developers, data engineers, analysts, ML and AI teams, security teams, and business users across the company. The team is in the middle of a significant architectural transition as Stripe grows. We are making Stripe's data lake a first-class citizen of the modern data ecosystem to support our growing scale and diverse workloads. What Makes This Role Compelling Foundational infrastructure with broad reach: The Datalake team's systems sit in the critical path of nearly every data workload at Stripe. Decisions affect petabytes of data, hundreds of production pipelines, and every engineering team that builds on Stripe's data lake. Multi-cloud architecture design and transition: You will lead the strategy to transition to a multi-cloud architecture and implement disaster recovery plans. Active, high-stakes, OSS-aligned architectural transformation: You will lead a multi-year migration to modern, open-source solutions like the Apache Iceberg. This is a technically deep project involving critical architectural choices at each step, from API design and compute engine integration to authorization models, where your opinions and technical influence will directly shape how the platform engages with the broader data infrastructure ecosystem. At Stripe you’ll have the scale of the large company and the agency to influence technical strategy and the roadmap Responsibilities Architect the unified Iceberg platform: Lead the technical design of a metastore service as it becomes the single source of truth for Iceberg table management across all compute engines — Spark, Trino, Flink, and PyIceberg. Define the API contracts, authorization model, per-table credential vending, and integration patterns that every data pipeline at the company will depend on. Lead compliance architecture: Partner with security and compliance teams to translate regulatory requirements into durable preventative technical controls — audit logging, access review infrastructure, data segregation, and lifecycle enforcement — built into the platform rather than bolted on. Drive cost and efficiency at petabyte scale: Identify systemic inefficiencies in storage layout, snapshot retention, and data lifecycle, and design automated, self-service tooling that scales without ongoing manual intervention from the team. Set the technical bar: Own critical design reviews, establish standards for reliability, security, and developer experience, and mentor senior engineers through high-stakes architectural decisions. Provide the technical judgment that keeps the platform moving fast without accumulating structural debt. Who You Are Minimum requirements 10+ years of professional software engineering experience Demonstrated track record of designing, building, and operating large-scale distributed storage or data infrastructure systems. Deep experience with object storage (S3, Azure Blob, or equivalent) — including IAM, access control policy design, lifecycle management, and operational practices at petabyte scale. Proven ability to lead complex, multi-quarter infrastructure projects end-to-end, including cross-team dependency management and coordinating migrations across many consuming teams. Strong background in authorization and access control design for distributed data systems. Preferred requirements 5+ years of Backend/Infrastructure Software Engineering experience. Experience safely executing large-scale data migrations with a strong instinct for sequencing, blast radius reduction, rollback, and data integrity validation. A strong developer experience sensibility: the ability to build abstractions that are ergonomic, well-documented, and actively reduce toil for the engineering teams that depend on your platform. In-office expectations Office-assigned Stripes in most of our locations are currently expected to spend at least 50% of the time in a given month in their local office or with users. This expectation may vary depending on role, team and location. For example, Stripes in Stripe Delivery Center roles in Mexico City, Mexico, Bengaluru, India, and Dublin, Ireland work 100% from the office. Also, some teams have greater in-office attendance requirements, to appropriately support our users and workflows, which the hiring manager will discuss. This approach helps strike a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility when possible. Pay and benefits Stripe does not yet include pay ranges in job postings in every country. Stripe strongly values pay transparency and is working toward pay transparency globally.

Who We Are 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 The Solutions Architecture (SA) organization helps Stripe's most strategic customers design and validate technical solutions that drive their business forward. Within SA, our team builds the tools, workflows, and custom technical assets that make the broader SA org more effective—turning individual ingenuity into org-wide capability. We are looking for AI Engineers who are energized by working close to the business and the users we serve. You'll operate as an embedded, high-context engineer focused on the highest-leverage opportunities across the SA org—building production-quality tooling, supporting our most strategic engagements, and shipping automation that meaningfully improves how Solutions Architects work every day. What You'll Do As an AI Engineer, you'll be embedded directly with the Solutions Architecture team—building alongside them, deeply understanding their workflows, and shipping tools and automation that permanently change how they operate. Your measure of success is SA productivity: the engagements you've accelerated, the workflows you've transformed, and the tools you've built that the org adopts as default. You'll ship code daily. You'll discover where SAs lose time and build high-impact solutions. You'll take what works for one person and scale it to work for the org. And when our most strategic customer engagements need custom technical assets, you'll build those too. This is a role for someone who wants to work at the intersection of engineering and business impact—close to customers, close to revenue, and building for people you can see using your work every day. Responsibilities Collaborate with Solutions Architects, SA leadership, Product, and Engineering to scope technical work and translate ambiguous business needs into well-defined deliverables Evaluate and integrate AI capabilities (LLMs, agents, workflow automation) where they provide genuine leverage—not for novelty, but for measurable productivity improvement Architect and build internal tools, agents, and automated workflows that accelerate SA and manager productivity across technical discovery, solution design, demoing, user engagements, territory/pipeline management, and product interlock Take high-potential tools and workflows built by SAs and managers and harden them into scalable, maintainable, production-grade solutions Identify patterns across SA workflows and proactively build solutions that address recurring friction Build custom demo environments, PoC applications, and technical assets for Stripe's most strategic customer engagements Document tools, architectures, and usage patterns so others can adopt and extend what you've built Debug, extend, and maintain backend systems across a variety of codebases and infrastructure Minimum Requirements 4+ years of experience as an engineer shipping production systems Strong backend engineering fundamentals: you can debug a failing system, trace issues across services, and reason about data flows Experience building and deploying AI agents, LLM-powered tools, or workflow automation beyond basic prompt engineering Experience scoping and delivering work with minimal oversight in a fast-moving, cross-functional environment Proficiency in at least two of: Ruby, Node.js, Python, or Next.js Familiarity with cloud infrastructure (AWS, GCP) including deployment, monitoring, and basic DevOps Experience building internal tools, developer platforms, or workflow automation Demonstrated ability to work across multiple codebases and technology stacks simultaneously Hands-on experience using AI/LLM tools in your engineering workflow—you're fluent with AI-assisted development but not dependent on it; you can reason through problems and debug without AI as a crutch Strong written and verbal communication skills; you can translate technical decisions for non-technical stakeholders and navigate cross-functional collaboration naturally Comfort with ambiguity—you can take a loosely-defined business problem, scope the engineering work, and ship iteratively without waiting for a perfect spec Preferred Qualifications Experience designing systems that non-engineers can build on top of or extend themselves (e.g., platforms, low-code frameworks, template systems) Experience in a Solutions Engineering, Sales Engineering, or GTM Engineering role—or a product engineering role where you worked closely with customers or go-to-market teams Familiarity with Stripe's products, APIs, or the payments/fintech domain Experience integrating with third-party platforms (Salesforce, Gong, etc.) Track record of building tools or systems that were adopted beyond your immediate team Background in consulting, professional services, or other roles that blend technical depth with business context Who You Are Beyond the technical requirements, we're looking for a specific kind of engineer: You want to be close to the business. You're energized by seeing your work directly impact how a sales team wins a deal or how a customer succeeds. You're a pragmatic builder. You ship working solutions quickly, iterate based on real usage, and know when "good enough now" beats "perfect later." You'd rather show a working prototype today than present a roadmap deck next quarter. You're a software engineer by practice. You can architect systems, debug production issues, write clean code, and reason about tradeoffs. AI is a tool in your belt, not a substitute for engineering judgment. You're a pattern recognizer. When you build something that works for one person, you immediately see how it generalizes. You think in reusable systems, not one-off scripts. You thrive without a traditional product team structure. No PRDs landing in your lap, no dedicated PM, no sprint ceremonies. You identify the highest-leverage problem, scope the work, and ship it. You're comfortable trading on-call rotations and rigid processes for autonomy and impact. You're a strong communicator. You can partner with SAs who are domain experts, understand their workflows deeply enough to build great tools, and explain your technical choices to leadership.

Who we are About Stripe Stripe is a technology company focused on improving the conditions for economic growth and prosperity. We build programmable financial infrastructure, rethinking from first principles how financial services should work, to make it easier and cheaper for any business to start and scale. More than 10 million businesses build on Stripe, spanning the economic frontier—from solo founders to established enterprises—united by a practical focus on growth. The most ambitious companies in the world use Stripe as core infrastructure to grow faster. They process trillions of dollars a year on Stripe, equivalent to around 1.6% of global GDP. While economic growth makes everyone better off, open markets also enable greater variety. When any business can easily serve a global customer base, the quality and diversity of products in the world increase, and craft and creativity are unleashed into the smallest niches. Our own growth is wholly contingent on the success of the businesses building on Stripe. We therefore invest back into our technology at an unusual rate. We make upgrades to our products every single day to deliver compounding gains to our customers. We maintain some of the most reliable APIs on the internet. We build entirely new pieces of financial infrastructure to enable new ideas. And our significant advances in risk and fraud infrastructure over many years are making the internet economy safer and more accessible. Though people at Stripe don’t tend to take themselves seriously, Stripe is a fairly serious place: our customers are depending on us for their livelihoods. We admire ambition, intensity, curiosity, humility, and rigor. The most effective people become knowledgeable about many domains besides their own. Any company is an applied exercise in understanding some aspect of society or the market. In working with so many (especially the new and innovative ones), we think that Stripe is one of the very best places to learn about how the world works. What you’ll do As an intern at Stripe you’ll work on projects across our stack that directly impact the way millions of businesses operate. You’ll own problems end to end with the support of your manager and teammates. It’s an opportunity to work alongside some of the most creative and technically rigorous engineers in the industry and learn how to ship high-quality work at scale. By contributing to Stripe’s codebase you’ll work across domains that give you insight into how the global economy works. Recent intern projects include expanding Stripe’s Payments Foundation Model capabilities to improve generalized anomaly detection, building more approachable fraud controls, creating safer payouts, and developing user-facing solutions that prevent costly pricing mistakes and make merchant checkout setup easier. Our internship program is competitive and the expectations are high. Responsibilities Operate as a real member of the team you join; engage in team discussions, decisions, and the technical design process. Write software that will be used in production, and has meaningful impact to Stripe’s business and users. Give and receive technical feedback through code reviews or design discussions Collaborate with other engineers and cross-functional stakeholders to proactively seek and incorporate feedback. Learn quickly by asking great questions, working with your intern manager and teammates effectively, communicating the status of your work clearly, and building with the latest AI tooling. Who you are Ambitious builder: You’re energized by building solutions without clear precedent and solving problems with far-reaching consequences. Successful Stripes are deeply curious, and prefer the joy of discovery to the comfort of certainty. Rigorous thinker: You appreciate that things worth doing are rarely simple. You enjoy working on problems that have never been tackled before. Adaptable problem solver: You adapt quickly and treat obstacles as opportunities. At Stripe we embrace kindness while encouraging Stripes to take measured risks and act boldly, even in the absence of consensus. Minimum requirements A strong fundamental understanding of computer science through pursuit of a Bachelor’s or Master’s degree in computer science, math, or a related discipline. Experience and familiarity with programming, either through side projects or classwork. We work mostly in Ruby, Java, Javascript, Go, and Scala. We believe new programming languages can be learned if the fundamentals and general knowledge are present. Experience from previous internships or other multi-person projects, including open source contributions, that demonstrate evaluating and receiving feedback from mentors, peers, and stakeholders. Ability to learn unfamiliar systems and form an understanding of those systems, through independent research and working with a mentor or subject matter experts. Ability to leverage AI tools to accelerate development while applying rigorous critical thinking and professional judgement to review, refine, and validate all outputs. Preferred qualifications At least 1 year of university education, or equivalent work experience. One or more areas of specialized knowledge (frontend, backend, infrastructure or other technologies) balanced with general skills and knowledge. Experience writing high quality pull requests, with good test coverage, and working knowledge to complete projects with minimal defects. Familiarity with navigating and managing your work in new code bases, with multiple languages. Clear written communication skills, with the ability to write clearly to explain your work to stakeholders, team members, and other Stripes.

Who We Are 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 The Core Change Management group is responsible for the systems that let every Stripe engineer ship code, configuration, and infrastructure changes safely and at high velocity. You will be embedded primarily on the Service Deployments team — the owners of Stripe's end-to-end code deployment platform — with regular collaboration with the Resource Automation and Feature Deployments teams. What Makes This Role Compelling You own the foundation of how Stripe ships software. The deployment platform sits in the critical path of every engineer's workflow at Stripe. The decisions you make affect thousands of deploys per day across hundreds of services, directly determining how fast and safely Stripe's product evolves. Technically rich, architecturally active. The team is executing several concurrent platform transformations: containerizing host-based services at scale, adding intelligent multi-service deploy pipelines, extending real-time anomaly detection to earlier stages of traffic shifts, and rebuilding deployment event infrastructure on top of a durable message bus. This is not maintenance work — the architecture is in motion. Broad surface area, real ownership. You will span the full stack from container scheduling and deployment orchestration business logic to the developer-facing internal platform UI. The problems are multi-layered: reliability, developer experience, performance, and safety all at once. Your judgment prevents incidents. The team's explicit goal is to drive down change-related incidents across Stripe by building better detection, smarter pipelines, and safer defaults. Your technical decisions have a direct and measurable safety impact on Stripe's reliability. Agency to shape technical strategy. As a Staff engineer on Service Deployments, you will set technical direction for the team's systems, author designs that span multiple teams, and be the person engineering managers and engineers turn to for the hardest deployment infrastructure questions. Responsibilities Own end-to-end technical delivery of large, ambiguous infrastructure projects — from initial design through production launch and long-term reliability. Author the design, sequence the work, unblock the team, and shepherd projects to landed impact. Architect the next generation of Stripe's deployment platform. Lead technical design of the deployment orchestrator's evolution — including multi-service dependency-aware autodeploy pipelines, Kubernetes-native deployment primitives, and fleetwide container migration — defining the API contracts, rollout strategies, and operational model that hundreds of teams depend on. Extend deploy anomaly detection. Evolve blue-green traffic analysis: extend coverage to earlier traffic-split stages, design API/method-based regression detection, and build a self-service onboarding system that makes anomaly detection the default for all supported service types. Own reliability and operational excellence for the deployment platform. Lead incident response; systematically reduce operational toil; and make reliability, security, and maintainability first-class properties of the systems you own. Build deployment event infrastructure. Own the deployment notification and event-publishing architecture — designing the event schema, durability model, and integration contracts that downstream systems rely on for observability and automation. Collaborate across Core Change Management. Partner with Resource Automation on projects that span deployment orchestration and cloud resource management (IAM, account provisioning, infrastructure automation), with Feature Deployments on change-safety tooling (feature flags, configuration management, change audit logs) that integrates with or depends on the deployment pipeline, and with the service mesh team on routing capabilities that enable advanced deployment patterns such as canary rollouts and merchant-priority traffic shaping. Set the technical bar. Own critical design reviews, establish standards for deployment safety and developer experience, mentor senior engineers through high-stakes architectural decisions, and advocate for the right abstractions — code that consuming teams can adopt without becoming deployment infrastructure experts. Decompose complexity for the team. Translate large, open-ended platform challenges into scoped, parallelizable work; help engineers grow by framing problems clearly and providing decisive technical guidance on the hardest questions. Who You Are Minimum Requirements 10+ years of professional software engineering experience , with a demonstrated track record of designing and shipping production infrastructure systems of significant scale and complexity. Proven ability to lead large, ambiguous infrastructure projects end-to-end — from technical design through delivery — including managing cross-team dependencies and coordinating migrations across many consuming teams. Deep expertise in distributed systems and deployment orchestration : strong foundations in how services are built, scheduled, and operated at scale, including rollout strategies, staged delivery, and failure modes. Hands-on experience with Kubernetes and container-based deployments , including service lifecycle management, workload scheduling, and the operational challenges of migrating large fleets from VM-based to containerized infrastructure. Strong background in service reliability and operational excellence : demonstrated ability to lead incident response, reduce toil, and build systems that are reliable, debuggable, and maintainable by a team. Track record of broad technical impact across multiple large systems : fluency across a complex codebase, force-multiplier effect through code review and mentorship, and the ability to set technical direction for a team rather than just execute within it. Preferred Requirements Background in deployment safety systems : anomaly detection, automated rollback, progressive delivery, or similar mechanisms that reduce the blast radius of bad deployments. Familiarity with event-driven architectures (Kafka or equivalent) applied to deployment lifecycle observability and notification. Experience with Infrastructure as Code at scale — Terraform or equivalent — particularly in the context of cloud resource governance and IAM management in AWS or Azure. Developer platform or internal tooling background : a strong developer experience sensibility and the ability to build abstractions that reduce toil for the engineering teams that depend on your platform. Change management and feature rollout systems : experience with feature flags, configuration distribution, or audit-log infrastructure that provides safety guardrails around production changes. Familiarity with service mesh concepts (canary deployments, weighted routing, traffic-splitting) sufficient to collaborate effectively with partner teams on routing capabilities that enable advanced deployment patterns. In-Office Expectations Office-assigned Stripes in most of our locations are currently expected to spend at least 50% of the time in a given month in their local office or with users. This expectation may vary depending on role, team and location. For example, Stripes in Stripe Delivery Center roles in Mexico City, Mexico, Bengaluru, India, and Dublin, Ireland work 100% from the office. Also, some teams have greater in-office attendance requirements, to appropriately support our users and workflows, which the hiring manager will discuss. This approach helps strike a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility when possible.

Who we are 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 Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We're looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our work is broad and varied, influencing how our products work (e.g., understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, and quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. We have a variety of Data Science roles and teams across Stripe and will seek to align you to the most relevant team based on your background. What you’ll do We’re looking for a Data Scientist to partner with our Local Payment Methods (LPM) engineering and product teams. You’ll play a key role in understanding, growing, and optimising our LPM business, leveraging data to make strategic business decisions. As Data Scientists at Stripe, it's our mission to ensure that the company strategy, products, and user interactions make smart use of our rich data, using techniques like machine learning, statistical modeling, causal inference, optimization, experimentation, and all forms of analytics. Who you are We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum requirements PhD, MSc or MA with 2 years, or BS or BA with 3 years of data science or quantitative modeling experience Proficiency in SQL and a computing language such as Python or R Experience in working with cross-functional teams to deliver results Ability to communicate results clearly and a focus on driving impact A demonstrated ability to manage and deliver on multiple projects with a high attention to detail Strong business acumen and experience in synthesizing complex analyses into actionable recommendations Proficiency with AI tools to accelerate model development, analysis, and coding Preferred qualifications Strong knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and experimentation Experience deploying models in production and adjusting model thresholds to improve performance Experience designing, running, and analyzing complex experiments or leveraging causal inference designs A builder's mindset with a willingness to question assumptions and conventional wisdom Experience with distributed tools such as Spark, Hadoop, etc. A PhD or MSc in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)

Engineering Manager, AI Conversation Platform Who we are 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 The newly formed Conversation Platform team aims to build a conversation platform for all merchants who use Stripe. We are doing so by (a) automating the easy tasks, and (b) assisting our users in the difficult tasks. Some examples include customizing the Stripe landing page to suggest bespoke integrations, allowing users to command the Stripe API in natural language, and resolving user issues automatically. We are developing RAG based systems on the latest LLMs as well as fine-tuning our own models. We’re an end-to-end team going from ideas to models to shipping in production. What you’ll do Responsibilities Driving an ambitious vision for AI/ML that benefits our users Setting the technical & process direction for the team based on business goals Brainstorm and coordinate product integrations with partner teams Proposing new ideas and building prototypes Be an integral part of a larger ML community internally & externally Hire & develop a world-class team to deliver high-quality ML systems. Coach engineers to help them grow in their careers and maintain a high bar Who you are We are looking for ML Engineering Managers who are passionate about using ML to improve products and delight customers. You have experience leading teams that develop streaming feature pipelines, build ML models, and deploy them to production, even if it involves making substantial changes to backend code. You are comfortable with ambiguity, love to take initiative, and have a bias towards action. Minimum requirements Have at least 4 years of experience managing ML teams Experience working as a Machine Learning Engineer, Applied Scientist or equivalent Individual Contributor. Lead by example in high-growth, high-impact, ambiguous environments Have experience building & shipping ML systems. Hold yourself and others to a high bar when working with production systems. Thrive in a collaborative cross-functional environment Preferred qualifications Experience in shipping LLM & RAG systems

Who we are 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 Our Applied ML team aims to reform how our users interact with Stripe. We are doing so by (a) automating the easy tasks, and (b) assisting our users in the difficult tasks. Some examples include helping our users resolve issues with Stripe faster or making it easier for our users to sign up and navigate Stripe. We are using the latest LLMs as well as fine-tuning our own models. We're an end-to-end team going from ideas to models to shipping in production. You can learn more about our team’s work from this recent talk . What you’ll do As a machine learning engineer, you will be responsible for analyzing opportunities, proposing ideas, training & evaluating ML models, running experiments, and deploying everything to production. You will also have the opportunity to contribute to and influence ML architecture at Stripe as well as be a part of a larger ML community. Responsibilities Our team operates fluidly and here are some problems you may tackle: How do we evaluate a system offline & online? How do we improve performance to match (and beat) humans? How do we ensure model quality doesn’t degrade online? Does fine-tuning an LLM give us better performance? What are the right OSS and in-house platforms we should invest in? And in the process you will: Develop pipelines and automated processes to train and evaluate models in offline and online environments Integrate ML models into production systems and ensure their scalability and reliability Collaborate with product and strategy partners to propose, prioritize, and implement new product features Engage with the latest developments in ML/AI and take calculated risks in transforming innovative ML ideas into productionized solutions Who you are We are looking for ML Engineers who are passionate about using ML to improve products and delight customers. You have experience developing streaming feature pipelines, building ML models, and deploying them to production, even if it involves making substantial changes to backend code. You are comfortable with ambiguity, love to take initiative, and have a bias towards action. Minimum requirements Have at least 3 years of experience shipping ML systems in production Hold yourself and others to a high bar when working with production systems Take pride in taking ownership and driving projects to business impact Thrive in a collaborative environment Preferred qualifications 5+ years of experience in full time software development roles Experience shipping LLM integrations to user products with high quality Experience operating in highly ambiguous environments Knowledge about driving a hypothesis from data

Who we are 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 Product and Risk Data Engineering is Stripe's single source of truth data engineering layer for Payments, Risk, and Product — we enable Stripe to confidently run, measure, and grow the business by making accurate information easy to access. We curate and maintain high-quality data warehouses and pipelines that serve as the authoritative foundation for product and financial activity across Stripe, powering analytics, ML capabilities, agentic workflows, and merchant-facing data interfaces. Beyond building data, we act as the internal experts in data technologies and partner with Data Platform to deliver high-quality, low-friction data processing frameworks. We also serve as the bridge between data producers and data consumers — championing best-in-class data engineering practices and guiding product teams on event-driven data API modeling — so that every team at Stripe can build, decide, and grow from a trusted, well-engineered data foundation. What you’ll do We're looking for a person who could contribute to the team by solving high-impact, cutting-edge data problems. The ideal candidate will be someone that has built data pipelines for large scale volume, is deeply knowledgeable of key tools including Airflow/Spark/Kafka/Flink, is empathetic, excels at building strong relationships, and collaborates effectively with other Stripe teams to understand their use cases and unlock new capabilities. Responsibilities Lead the technical outcomes for a team of ambitious, talented engineers, providing mentorship, guidance, and support to ensure their success Partner with our recruiting team to attract and hire top talent Deliver cutting-edge data pipelines that scale to users' needs, focusing on reliability and efficiency Develop strong subject matter expertise and manage the SLAs of data pipelines and full stack web applications that support critical stakeholders Collaborate with product managers and peers across the company to create/improve canonical datasets and data warehouses, use golden paths, and ensure Stripes and customers are using trustworthy data Leverage AI/LLM and Agents at scale to produce and analyze high-quality data on ambiguous problems Have the opportunity to drive the execution of key data initiatives for Stripe, overseeing the entire development lifecycle from planning to delivery while maintaining high standards of quality and timely completion Foster a collaborative and inclusive work environment, promoting innovation, knowledge sharing, and continuous improvement within the team Who you are We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum requirements This is a Staff-level role — that typically means 10+ years of experience building and operating data systems, pipelines, warehouses, infrastructure, and leading teams to deliver exceptional solutions A strong engineering background and passion for data as well as prior experience with writing and debugging data pipelines using a distributed data framework An inquisitive nature in diving into data inconsistencies to pinpoint issues, and resolve deep rooted data quality issues Knowledge of a backend development language (such as Scala, Java, or Go) and strong SQL experience Extreme customer focus, with a commitment to partnering with product, leaders across the business, and other Stripe engineers to understand their use cases Effective cross-functional collaboration, with the ability to think rigorously, communicate clearly, and make or coordinate difficult decisions and trade-offs Thrive with high autonomy and responsibility in an ambiguous environment Ability to foster and work in a healthy, inclusive, challenging, and supportive work environment Preferred qualifications Our stack is made up of Iceberg, Kafka, Change Data Capture, Flink, Spark, Airflow, Hive Metastore, Pinot, Trino, and AWS Cloud - experience with all or some of these tools is a huge plus Influencing open-source contributions Experience creating and maintaining data marts / warehouses to power business reporting needs Experience collaborating with Product, Go-To-Market, or Sales / Marketing teams Genuine enjoyment of innovation and a deep interest in understanding how things work, with the ability to question and direct architectural decisions Strong written and verbal communication skills for various audiences, including leadership, users, and company-wide