Software Engineer Data Infrastructure in United States

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. As a Data Engineer, you’ll be responsible for laying the foundation for a best-in-class analytics function. You’ll partner closely with our engineering team and business stakeholders to ensure that our analytics stack and processes meet the business needs today with an eye towards the future. Visit our Vanta Engineering Blog to learn more about what our team is working on! What you’ll do as a Senior Data Engineer at Vanta: Design and deploy data infrastructure needed to drive data-driven decision-making solutions Design and implement complex data orchestration models, modeling metadata, scaling reporting tools for data science and ML products users Be the company’s expert on data administration, data management and scalable data systems Write highly tuned, scalable SQL queries running over large-scale, heterogeneous data warehouses Work with the Product and Enterprise Engineering system teams to structure source systems for reporting consumption across the enterprise Help maintain CDC pipelines to power customer reporting Help develop front end applications to expose analytical data sets enterprise wide How to be successful in this role: Have at least four years of experience working with data and two years of experience in Software Engineering or a related field. Have experience with common analytics tooling (e.g. Stitch/Fivetran, Snowflake/BigQuery/Redshift, dbt, Airflow, Dagster). Have good working knowledge of AWS data infra systems and Terraform. Bring a system-oriented and software engineering mindset to the Data Engineering practice. We’re looking to build frameworks that manage data, and minimize bespoke queries Deep kn

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role The Data Platform builds infrastructure and tools that enable Ramp to realize business value from data. We partner closely with stakeholder teams to build this infrastructure and the applications on top of it. This role is particularly focused on building platforms that support the data science development lifecycle. You’ll partner with applied scientists, AI engineers, Risk engineers, and other ML developers on building infrastructure and tools that enable and accelerate the development of machine learning models. What You’ll Do Build and integrate the components of Ramp's Analytics Platform and Machine Learning Platform. Build tools that improve the agility and data experience of Ramp's Applied Scientists, AI Engineers, and Risk Engineers. Collaborate with stakeholder teams on building and productionizing machine learning applications. Build reliable, scalable, maintainable, and cost-efficient systems across the stack. What You Need Experience with workflow orchestrators like Airflow, Dagster, or Prefect. Experience building infrast

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Security Engineering is the engineering function inside the Plaid security org that focuses on developing the industry-leading security systems and infrastructure. Security Engineering owns most of Plaid’s security-related infrastructure: secure data storage, key management systems, internal identity platform, internal authentication systems, internal permission management, and internal authorization service. We develop solutions across data encryption, key management, access control, and data loss prevention to protect sensitive consumer data. We believe in the Zero Trust security model and are always looking for ways to improve our authentication and access control platforms. About the role You will develop security capabilities to secure Plaid infrastructure and to secure sensitive data access. You will own, maintain, and build Plaid’s security infrastructure and services like Key Management System and Secure Token Service. You will consult with product engineers to ensure Plaid services meet security standards. You will help educate and support other engineering teams to improve security in their own products and services. You will assist with Plaid’s incident response and security awareness pro

About the Team The Intelligence & Investigations Engineering team builds systems that detect, analyze, and disrupt abuse across OpenAI’s products. We partner closely with the Child Safety team and cross-functional groups to protect users while advancing OpenAI’s goal of developing AI that benefits everyone. About the Role As a Fullstack Engineer focused on child safety, you’ll build data-intensive, AI-powered applications and infrastructure that enable operators and investigators to work effectively and responsibly. You’ll adapt quickly in ambiguous, fast-moving environments to deliver well-crafted, reliable tooling for high-severity safety work. *Candidates should understand this role involves exposure to sensitive and egregious content. In this role, you will: 4+ years of experience as a software engineer Prototype, build, and maintain intelligence systems that detect, triage, and enable efficient human review of possible high severity harm Work hand in hand with operators and investigators, designing and delivering systems that enable them to do their work faster, more accurately, and more safely. Develop across the stack: UIs, services, pipelines, and anything else required to solve the problems we face. Interact with partners across Product Policy, Platform Integrity, Safety Systems, and Research Contribute to the team’s technical strategy, especially for child safety related tools and systems Report on impact in a data-driven fashion You might thrive in this role if you: Have a strong software engineering foundation and enjoy owning systems end-to-end—from infrastructure and data ingestion to frontend tooling Are energized by working at the frontier of AI capabilities, integrating new models and APIs into practical systems Have experience building and operating large-scale data pipelines or search/retrieval systems Are proficient in Python and/or TypeScript, and familiar with tools like Spark, Kafka, Flink, data warehouses, and SQL Take a product-minded ap

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. The Billing & Payments Platform team builds Snowflake's central data repository and infrastructure for customer resource consumption, revenue processing, invoicing, and reporting. Our systems power Snowflake's business and enable every other engineering team — and the architectures we ship double as reference patterns for our customers building on Snowflake. Computing Snowflake's bills, at its core, is a challenging distributed systems problem: real-time usage metering across every cloud and region, and supporting an ever-evolving catalog of pricing models — including the new commercial constructs we are inventing for Cortex AI, Snowflake Intelligence, and the broader agentic AI portfolio . Our applications must meet strict requirements for accuracy, auditability, and low-latency processing. This is a deeply cross-functional role. You will partner daily with Product, Finance, Legal, Growth, Go-to-Market Systems, Snowsight UI, Cortex AI, and product engineering teams across Snowflake to deliver experiences that customers and internal stakeholders depend on every day. What You'll Do As a Senior Software Engineer on Billing Platform, you will: Own medium-sized projects end-to-end — from design through launch and operation — and contribute as a key engineer on large, multi-

We are a global team of innovators and pioneers dedicated to shaping the future of observability. At New Relic, we build an intelligent platform that empowers companies to thrive in an AI-first world by giving them unparalleled insight into their complex systems. As we continue to expand our global footprint, we're looking for passionate people to join our mission. If you're ready to help the world's best companies optimize their digital applications, we invite you to explore a career with us! Your Opportunity At New Relic, we provide our customers with real-time insights, so they can innovate faster. Our software provides deep observability across the stack, enabling software teams to solve their customer’s problems, accelerate digital transformation, and make DevOps work. You will be at the heart of the teams supporting New Relic’s infrastructure and will work on a team that provides global service mesh and load balancing solutions. We provide these services on-premises, as well as using our multi-cloud infrastructure. We support each other to do our best work through positive communication and continuous improvement. What You’ll Do As a key member of our Infrastructure team, you will design and operate a scalable, resilient ingress data plane that directly impacts the value we provide to our customers. By ensuring the stability and performance of our global service mesh and load balancing solutions, you drive the foundational reliability that the entire New Relic organization depends on to deliver real-time insights. You will leverage advanced automation and infrastructure-as-code to accelerate development speed, allowing our engineering teams to ship safe, incremental changes across a massive fleet with confidence. Your work in evolving our DNS and CDN infrastructure is not just about maintenance; it is about creating a seamless, high-performance environment that enables innovation at scale. Through deep collaboration with Product, Design, and partner platform t

Overview: The Data Acquisition team within the Foundations organization at OpenAI is responsible for all aspects of data collection to support our model training operations. Our team manages web crawling and GPTBot services and works closely with Data Processing, Architecture, and Scaling teams. We are looking for a skilled Software Engineer to join our Data Acquisition team. Responsibilities: Own and lead engineering projects in the area of data acquisition including web crawling, data ingestion, and search. Collaborate with other sub-teams, such as Data Processing, Architecture, and Scaling, to ensure smooth data flow and system operability. Work closely with the legal team to handle any compliance or data privacy-related matters. Develop and deploy highly scalable distributed systems capable of handling petabytes of data. Architect and implement algorithms for data indexing and search capabilities. Build and maintain backend services for data storage, including work with key-value databases and synchronization. Deploy solutions in a Kubernetes Infrastructure-as-Code environment and perform routine system checks. Conduct and analyze experiments on data to provide insights into system performance. Qualifications: BS/MS/PhD in Computer Science or a related field. 4+ years of industry experience in software development. Experience with large web crawlers a plus Strong expertise in large stateful distributed systems and data processing. Proficiency in Kubernetes, and Infrastructure-as-Code concepts. Willingness and enthusiasm for trying new approaches and technologies. Ability to handle multiple tasks and adapt to changing priorities. Strong communication skills, both written and verbal. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an

About the Team: Compute Infrastructure builds the platform that turns enormous amounts of compute into a reliable engine for frontier AI. We design, provision, schedule, operate, and optimize the systems that connect accelerators, CPUs, networks, storage, data centers, orchestration software, agent infrastructure, developer tools, and observability into one coherent experience for researchers and product teams. Our work spans the entire stack: capacity planning and cluster lifecycle, bare-metal automation, distributed systems, Kubernetes and scheduling, deep system optimization, high-performance networking, storage, fleet health, reliability, workload profiling, benchmarking, and the developer experience that lets teams use enormous compute systems with confidence. At this scale, small improvements to communication, scheduling, hardware efficiency, or debugging workflows can compound into meaningful research velocity. We are hiring across Compute Infrastructure rather than for a single narrow team, and we use this opening to match strong engineers to the problems where they can have the most leverage. About the Role We are looking for engineers who want to build the compute platform behind OpenAI's research and products. You may not be the strongest in low-level systems, high-performance computing, distributed infrastructure, reliability, CaaS, agent infrastructure, developer platforms, tooling, or the user experience around infrastructure. What matters is that you can reason carefully about complex systems, write durable software, and raise the quality and velocity of the people around you. Depending on your background and interests, you might work close to hardware, close to users, on CaaS and agent infrastructure, or on the control planes and data planes in between. You could help bring new supercomputing capacity online, optimize training workloads from profiler traces and benchmarks, improve NCCL and collective communication behavior, reason about GPUs, NICs, t

About the team The Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth. About the role As a software engineer on the Fleet High Performance Computing (HPC) team, you will be responsible for the reliability and uptime of all of OpenAI’s compute fleet. Minimizing hardware failure is key to research training progress and stable services, as even a single hardware hiccup can cause significant disruptions. With increasingly large supercomputers, the stakes continue to rise. Being at the forefront of technology means that we are often the pioneers in troubleshooting these state-of-the-art systems at scale. This is a unique opportunity to work with cutting-edge technologies and devise innovative solutions to maintain the health and efficiency of our supercomputing infrastructure. Our team empowers strong engineers with a high degree of autonomy and ownership, as well as ability to effect change. This role will require a keen focus on system-level comprehensive investigations and the development of automated solutions. We want people who go deep on problems, investigate as thoroughly as possible, and build automation for detection and remediation at scale. In this role, you will: Build and maintain automation systems for provisioning and managing server fleets. Develop tools to monitor server health, performance, and lifecycle events. Collaborate with clusters, networking, and infrastructure teams. Partner with external operators to ensure a high level of quality. Identify and fix performance bottlenecks and inefficiencies. Continuously improve automati

About the Team We’re hiring Software Engineers to join our broader Infrastructure organization, which supports multiple high-impact teams. Depending on your interests and experience, you could work on one of several focus areas—including Core Distributed Systems, Reliability Engineering, Observability, Developer Productivity or Cloud Infrastructure. About the Role All teams are deeply collaborative, work on mission-critical services, and are responsible for building distributed, scalable infrastructure to bring OpenAI’s technology to the world through products like ChatGPT and the OpenAI API. You’ll work closely with stakeholders to understand infrastructure, data and compute needs, setting the technical strategy that supports cutting-edge research and product development. This is a critical role for someone who is passionate about solving complex engineering problems at scale, ensuring their performance, scalability and reliability Team Focus Areas Distributed Systems: Owning and building important, highly scalable, available, performant, and reliable distributed systems (and their building blocks) to power the entire stack at OpenAI Systems Engineering: Work across layers of the stack—debugging system bottlenecks, evolving core infrastructure, and solving novel problems in performance and scalability. Reliability Engineering: Build scalable, fault-tolerant systems and lead efforts around service health, incident response, and resilience. Observability: Design and maintain observability tooling (metrics, logs, tracing) to give teams visibility into production systems at scale. Developer Productivity: Create tools, environments, and workflows that help engineers ship high-quality software faster and more safely. Cloud Infrastructure: Own the cloud-native infrastructure (compute, networking, storage) that underpins all services and research workloads. Databases: Building high performance, distributed database systems that power all of OpenAI's product stack. In this

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. Job Summary We are looking for an experienced Growth Infrastructure Engineer to build and maintain the technical backbone that enables scalable growth experiments, high-performance data pipelines, and automated systems that drive user acquisition, engagement, and product iteration. This role sits at the intersection of growth, product, and infrastructure — combining deep technical engineering with experimentation and data-driven optimization. You will collaborate with product, data science, and backend teams to ensure that growth initiatives run smoothly and scale efficiently across systems. Key Responsibilities Growth Infrastructure & Systems Design, implement, and maintain scalable infrastructure that supports growth and experimentation needs. Build and optimize analytics pipelines to capture key product and growth metrics (acquisition, activation, retention, etc.). Develop automated workflows for user onboarding, campaign delivery, and performance tracking. Experimentation & Optimization Support A/B testing frameworks and integrate them into production systems. Enable reliable data collection and evaluation for growth experiments. Automate deployment and rollout of growth feature flags and tests. Cross-Functional Collaboration Partner with Growth Product Managers, Data Engineers, and Analysts to define technical requirements for growth initiatives. Translate business goals into technical specifications and system designs. Provide guidance on performance, reliability, and scalability trade-offs. Monitoring & Reliability Implement monitoring and alerting for growth infrastructure services. Troubleshoot production issues and optimize for uptime and performance. Ensure data quality and consistency for report

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but operational in how we execute, and we support every product and research effort at OpenAI. Our tenets include prioritizing for impact, enabling researchers and developers, preparing for future transformative technologies, and fostering a strong, collaborative security culture. About the Role OpenAI is seeking a Security Software Engineer to join the Infrastructure Security (InfraSec) team. InfraSec safeguards the core of OpenAI’s research and production environments—GPU supercomputing clusters, multi-cloud infrastructure, datacenters, networking, storage, and the critical services that power our frontier AI models. Our charter spans everything from bare-metal hardware and firmware to Kubernetes clusters, service meshes, and the data pathways that carry highly sensitive model weights and user data. As a Security Software Engineer, you will design and build critical foundational services, such as authentication systems, egress/ingress proxies, access brokers, and key management platforms, that demand high standards of reliability, scalability, and software craftsmanship. These systems form the security backbone of OpenAI’s supercomputing environment and must remain robust under intense scale and adversarial pressure. In this role, you will: Architect and implement production-grade security services (e.g., auth services, access brokers, secure proxies, key-management infrastructure) that provide strong guarantees across hardware, operating systems, Kubernetes, networks, and CI/CD. Partner with infrastructure and research engineers to embed security into high-performance compute clusters, enabling rapid model training and deployment without compromising protection. Develop automation and detection tooling to continuously identif

About the team Online Data builds and operates Habitat, the single product surface of Online Data and the system of record for OpenAI’s online user data. As OpenAI’s scale and product requirements evolve, Habitat is becoming a full-stack, one-size-fits-most database platform with end-to-end ownership of: Provisioning and developer experience APIs and guardrails Scaling, performance, and reliability Data movement, caching, routing, and placement Privacy enforcement and access control Change Data Capture (CDC) as a first-class primitive The foundation for future storage backends You’ll work on the core online database platform behind OpenAI’s products, building and operating Habitat services that handle high-QPS, latency-sensitive workloads across regions. You’ll partner closely with internal platform and product teams to ship safe, reliable systems, then push them to be faster and more cost-efficient through better caching, routing, observability, and operational tooling. This is a critical role for engineers who like owning hard distributed-systems problems end to end and sweating the details from p99 latency to production operations at massive scale. In this role, you will Design and build core abstractions spanning storage, caching, routing, CDC, and privacy enforcement Own a major surface area end to end, from product and API design to operational excellence Improve latency, correctness, and cost efficiency for real production workloads at massive scale Build strong instrumentation, debugging workflows, and developer-first tooling Collaborate closely with internal product and infrastructure teams to understand requirements and ship pragmatic solutions Participate in an on-call rotation and raise the bar on reliability while aggressively improving performance and usability You might thrive in this role if you have A strong track record building and operating high-scale backend or data-intensive distributed systems in production Excellent systems judgment and the a

About the Team ChatGPT is a rapidly evolving system: new capabilities ship continuously, product surfaces change quickly, and usage patterns shift week-to-week. Supporting that pace requires infrastructure that can handle real production constraints—high concurrency, unpredictable traffic patterns, complex dependency graphs, and frequent change. The ChatGPT Infrastructure team builds and operates the platforms that enable fast iteration without compromising performance or reliability. We design shared systems, data paths, rollout mechanisms, and reliability guardrails that teams rely on to ship changes to ChatGPT at scale. We focus on high-leverage infrastructure: primitives and “golden paths” that incorporate operational lessons as defaults, so engineers don’t need to rediscover failure modes, latency pitfalls, or integration issues each time they build something new. About the Role We’re hiring Senior and Staff Engineers to design and build infrastructure systems that underlie ChatGPT and multiply the effectiveness of teams building user experiences. This is not a support-only role. It’s a platform-building role: you’ll define interfaces, develop core abstractions, and create tooling to make safe, fast iteration the norm. Your work will reduce friction, prevent regressions, improve performance, and ensure systems scale gracefully as the product grows. Where You Can Have Impact You might work on one or more of the following areas (without being restricted to any single area): Platform foundations & frameworks: Core libraries, service frameworks, and shared components that standardize system building, integration, and evolution. Scalability & performance primitives: Patterns and infrastructure that reduce tail latency, improve throughput, and keep costs predictable as demand increases. Reliability guardrails: Mechanisms that prevent outages by design—rate limiting, load shedding, dependency isolation, backpressure, safe fallbacks, and robust regression contr

About the Team The Platform Analytics team builds the systems OpenAI researchers use to understand the quality and behavior of the models we train including what models are doing, why they behave in a particular way, and how that behavior changes across experiments. Neptune is a core part of this work. It ingests, stores, queries, and visualizes large volumes of metrics from pretraining, post-training, and reinforcement learning. Hundreds of researchers depend on these systems in their daily work to compare experiments, debug unexpected behavior, and decide what to try next. Our scope is broader than metrics. We also build platforms that help researchers analyze samples, traces, evaluation results, and other structured or unstructured data through dashboards, APIs, and increasingly agent-driven workflows. These systems need to remain fast, reliable, and understandable as the scale and complexity of research change quickly. We are not trying to become a consulting team that builds a separate solution for every research project. We work directly with researchers to understand recurring problems, then turn them into reusable infrastructure and platform capabilities that many teams can build on. About the Role We’re looking for a hands-on experienced software engineer who can take ownership of a critical system and drive it from problem definition through production adoption. This person should be able to own a platform such as CacheHouse end to end: define its technical direction, design its data model and storage architecture, integrate it with several research dashboards and workflows, guide one or two engineers, and ensure the system works reliably for its users. The right candidate should already bring the technical judgment, ownership, and execution expected at this level. The primary learning curve should be OpenAI’s stack and research problem space, not learning how to lead a complex engineering effort or deliver a production system. You will work directly with