It Storage Engineer in United States

About Datadog: We're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale—trillions of data points per day—providing always-on alerting, metrics visualization, logs, and application tracing for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Opportunity: Datadog’s Staff Engineers are our technical leaders operating at the forefront of technology, building solutions that take us through at least our next five years of growth. They do this in three major ways: As individual contributors, they bring world class technical abilities to deliver industry leading systems in areas such as data visualization, virtual runtime profiling, and planet scale streaming. As technical leaders they bring experienced technical breadth and communication skills to tackling design and architectural problems spanning the organization, charting the right course, then leading delivery. In both roles they participate in the staff engineering community and help us learn from what the industry is doing and what we've built before, and so improve company wide standards around software and systems engineering. Some examples of projects a staff engineer may own include designing and building a new data storage engine handling hundreds of millions of records per second, being the lead engineer building a new product like synthetics or profiling, or rebuilding a critical service to handle the next two orders of magnitude of scale. What You'll Do: Be the technical owner of multiple pieces of critical architecture in your area of the business Own delivery of the systems you architect from beginning-to-end, doing what it takes to get things shipped and at full scale in production Dive deep into performance of systems; inventing new approaches that bring efficiency at scale Who You Are: You have a BS/MS/P

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . As a principal engineer on the Online Systems team, you’ll join a team that powers Pinterest’s most business-critical online systems at massive scale, driving the reliability, efficiency, and evolution behind every core Pinner and Advertiser experience. You'll lead major efforts like multi-region deployment and Kubernetes migration, set the standard for operational excellence, and define the long-term vision for our online serving infrastructure, supporting machine learning and product innovation across the company. This is an opportunity for high-impact technical leadership, broad visibility, and cross-functional influence at the heart of Pinterest’s platform. What you’ll do: Improve reliability, scalability and infra efficiency for Pinterest’s critical online systems across storage and caching, online service and realtime analytics syste

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . The Data Product Platform is mission-critical to accelerating data-driven decision-making at Pinterest on the foundation of 100s of thousands of tables and an exadata-scale data warehouse. We strive to provide effortless, efficient, and reliable data products and platforms that power the entire company. We achieve this by investing in three core areas: Data Warehouse: Building and managing the foundational data warehouses that enable key analyses across both our core engagement and monetization products. Analytical Velocity: Creating powerful analytical tools that empower internal data users to leverage our vast data assets and capable infrastructure effectively. Data Governance: Defining and implementing the data governance policies and tools necessary to ensure the responsible, efficient and compliant storage and handling of all data. We are s

About the Team OpenAI’s Applications Engineering organization builds and operates the products (such as ChatGPT & Codex) that bring our cutting-edge research to millions of users and developers worldwide. The Applied Foundations team owns the core product and platform layers that make those experiences possible — from identity & access, to safety to payments & commerce across all of our apps. Our teams span product engineering, infrastructure, and safety, working together to deliver technology that is reliable, secure, and trusted at global scale. About the Role We’re hiring Backend Software Engineers to design and implement safe services and infrastructure that power our core products. What You’ll Do Architect, build, and improve scalable backend systems and APIs. Drive performance, reliability, and safety across distributed services. Implement data storage, retrieval, compute, and integration solutions. Participate in long-term architectural planning and technical design reviews. Collaborate with cross-functional teams to design solutions that protect against and mitigate adversarial attacks without compromising user experience. You Might Thrive Here If You: Have strong experience with distributed systems, APIs, and backend languages (e.g., Go, Python, Rust, C++). Have experience setting up and maintaining production backend services and data pipelines. Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed. Enjoy building resilient services that handle large scale and complexity. Are self-directed and enjoy figuring out the best way to solve a particular problem Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done. 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

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

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. Our team builds and operates Snowflake's Streaming Platform — the core infrastructure responsible for bringing data into Snowflake continuously and at scale. This includes Snowpipe Streaming and Datastream, services used by large set of enterprise customers to move mission-critical data in real time. Data is the fuel powering the new enterprise AI world, and we are the team responsible for getting it there reliably, continuously, and fast. Responsibilities Design, build, and maintain core components of Snowflake's streaming ingestion platform Improve service reliability, scalability, and latency under high-throughput production workloads Debug and resolve incidents in a distributed, multi-tenant cloud service Contribute to the design and evolution of streaming APIs, SDKs, and server-side protocols Write comprehensive tests including unit, integration, and chaos/fault-injection scenarios Collaborate with partner teams (storage, query, compute) on cross-cutting platform concerns Participate in code reviews, on-call rotations, and architecture discussions Required Qualifications 3–5 years of software engineering experience on large-scale distributed systems or cloud services Strong proficiency in Java or C++ Deep understanding of distributed systems concepts: consistency, faul

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role Sentry provides developer-first observability to over 4 million developers worldwide. The Events Analytics Platform (EAP) team is at the heart of that mission: it powers how all of Sentry's event data, such as errors, transactions, spans, profiles, replays, and metrics, is stored, queried, and analyzed. It also powers Sentry's latest AI push, Seer. The EAP team makes it possible for developers to efficiently search and debug across massive volumes of data, providing the context needed to understand and fix issues quickly. This team is also a cornerstone of Sentry's long-term strategy to become a context assembly and telemetry platform that unifies different signals so developers can see the complete picture. As an engineering manager on the EAP team, you will lead a group of engineers building and scaling one of Sentry's most critical data platforms. You will be responsible for driving architectural evolution, ensuring system stability, and mentoring a talented team. This is a highly visible leadership role with direct ties to Sentry's long-term product and platform strategy. What you'll do Grow and develop a team of engineers with high expectations for ownership and impact Set the technical and strategic direction for the team, balancing short-term stability with long-term architectural evolution Drive development of core EAP features, including support for complex analytical queries, dynamic routing logic across fidelity levels, storage and compute separation, and modern patterns for analytical storage Ensure EAP can support the workload demands of AI agents and MCP servers that unlock new AI capabilities fo

We are hiring a Security Software Engineer to design and implement the hardware-backed security foundations used across OpenAI’s device ecosystem. A central focus of this role is hardening the boundary between our policy systems and the HSMs that protect sensitive cryptographic keys. This boundary determines which operations may be performed, what may be signed, which policies must be satisfied, and how changes to trusted software and policy are authorized. You will develop security-critical software and firmware within, or immediately adjacent to, an HSM trust boundary. Depending on your background, this may include HSM trusted applications, firmware services, cryptographic mechanisms, device drivers, PKCS#11 components, secure-provisioning protocols, or signing-policy enforcement systems. This is a hands-on software-engineering role. You will be expected to design systems, write and review production code, debug across hardware and software boundaries, and carry projects from initial requirements through deployment. It is not an HSM administration, PKI operations, compliance, or architecture-only position. In This Role, You Will Design and implement security-critical software and firmware for HSMs, secure elements, trusted execution environments, and hardware roots of trust. Build and harden the policy-to-HSM boundary responsible for authorizing certificate issuance and cryptographic signing operations. Develop HSM trusted applications, firmware components, host interfaces, device drivers, SDKs, or cryptographic service integrations. Implement or extend cryptographic interfaces such as PKCS#11, OpenSSL providers or engines, platform key-storage APIs, or comparable hardware-security interfaces. Build firmware and software that cryptographically enforces key generation, provisioning, usage, rotation, recovery, and destruction policies. Design and implement HSM-backed certificate authority, code-signing, key-management, and device-identity systems. Develop end-to-end

About Mixpanel Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build. By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working, diagnose what’s not, and decide what to build next. Learn more at mixpanel.com . About Mixpanel Mixpanel turns data clarity into innovation. Trusted by more than 29,000 companies, including Workday, Pinterest, LG, and Rakuten Viber, Mixpanel’s AI-first digital analytics help teams accelerate adoption, improve retention, and ship with confidence. Powering this is an industry-leading platform that combines product and web analytics, session replay, experimentation, feature flags, and metric trees. Mixpanel delivers insights that customers trust. Visit mixpanel.com to learn more. About The Team Mixpanel Engineering is a small, fast-moving team focused on delivering real value to customers. We build powerful AI-powered product analytics while obsessing over clarity, simplicity, and delight. Engineers here own problems end to end. You can move across the stack to ship impact without being blocked by silos or heavy process. Product innovation drives our business, and product engineering teams own that responsibility. Our OLAP engine queries over 500 trillion events; a typical blob storage system we interact with processes 300 PiB/month at 1.2 Tbps sustained, and we run many of them across the world. The Data Runtime team owns the data execution layer that powers every Mixpanel product. We ensure that every customer query runs fast, cheap, and reliably, at any scale. This is an exciting time to join. Mixpanel's agentic and AI-first products are driving rapid growth in query volume, and Data Runtime is making the big bets that power it. We’re investing in elastic query compute and a distributed file cache that will let us scale query workloads dramatically without scaling cost with them. We

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Baseten is seeking talented and experienced Software Engineers to join our Observability team within the Infrastructure organization. As an early member of the Observability Team, you will be pivotal in building and shaping the observability experience for our internal and external customers. By joining this team, you’ll have a direct impact on the reliability and operational excellence of Basetens product systems. As Baseten scales its infrastructure across different cloud providers and diverse hardware, the volume and complexity of operational data is growing by orders of magnitude. This team is responsible for building high-throughput ingest pipelines, cost-efficient storage, and agentic diagnostic tools to ensure that we can detect, diagnose, and resolve issues in minutes rather than hours, even as the systems they operate become more complex. RESPONSIBILITIES Design and build scalable telemetry ingest and storage pipelines for metrics, logs, and traces across Baseten’s multi-cloud infrastructure Own and evolve core observability platforms, driving migrations and architectural improvements that improve reliability, reduce cost, and scale with organizational growth Build instrumentation libraries, SDKs, and integrations that make it easy for engineering teams to emit high-quality telemetry from their services Drive alerting and SLO infrastructure that enables teams to define, monitor, and respond to reliabi

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role Sentry provides developer-first observability to over 4 million developers worldwide. The Events Analytics Platform (EAP) team is at the heart of that mission: it powers how all of Sentry's event data, such as errors, transactions, spans, profiles, replays, and metrics, is stored, queried, and analyzed. It also powers Sentry's latest AI push, Seer. The EAP team makes it possible for developers to efficiently search and debug across massive volumes of data, providing the context needed to understand and fix issues quickly. This team is also a cornerstone of Sentry's long-term strategy to become a context assembly and telemetry platform that unifies different signals so developers can see the complete picture. As an engineering manager on the EAP team, you will lead a group of engineers building and scaling one of Sentry's most critical data platforms. You will be responsible for driving architectural evolution, ensuring system stability, and mentoring a talented team. This is a highly visible leadership role with direct ties to Sentry's long-term product and platform strategy. What you'll do Grow and develop a team of engineers with high expectations for ownership and impact Set the technical and strategic direction for the team, balancing short-term stability with long-term architectural evolution Drive development of core EAP features, including support for complex analytical queries, dynamic routing logic across fidelity levels, storage and compute separation, and modern patterns for analytical storage Ensure EAP can support the workload demands of AI agents and MCP servers that unlock new AI capabilities fo

Join the MongoDB Server Query Optimization team, and help us build a world-class distributed open-source query optimizer. Our team plays a crucial role in the experience and performance of data processing. We are responsible for the MongoDB Query Language and the lifecycle of each query, through parsing, optimization and plan selection. We have a presence across the US and Europe including New York, Dublin, Seattle, Palo Alto, and Chicago. We support office-based and remote work and align projects with convenient work hours for each time zone. We have tons of interesting problems to solve with a direct impact on users for transactional, time-series, and analytical workloads. The team is endeavoring to systematically rewrite every major component of our optimization and execution systems. We need your help to design and build the heart of a distributed, flexible schema, document database. ​​This role can be based out of our US offices or remotely in the North America region. Candidate Profile 10+ years of experience in data management systems, distributed systems, or large-scale backend engineering Experience with building production-level code with a large user base, robust design structure and rigorous code quality Degree in Computer Science or similar field, or equivalent practical experience, with strong competencies in data structures, algorithms, and software design/architecture Experience with large code bases written in C++ or another systems programming language. You'll need to trace down defects, estimate work complexity, and design evolution and integration strategies as we rewrite different components of the system A strong foundation in core database internals is essential. While direct experience in query optimization is a massive bonus, it is not a prerequisite. We are also excited to meet candidates with strong backgrounds in compilers, language transpilers, or distributed storage systems Position Expectations Innovate in the area of flexible schema d

About the Team OpenAI's data and storage infrastructure spans data platforms, online databases, and file/object storage. These systems underpin data ingestion and processing, durable persistence, indexing and retrieval, and product file experiences. As frontier models and agents evolve how they use memory, history and snapshots, the underlying architecture increasingly shapes the capabilities products can deliver—and their latency, reliability, cost and efficiency. About the Role We are looking for a technically deep TPM to independently define and lead multiple programs across data platforms, online databases and storage infrastructure. You will connect model, product and data-consumer requirements to architecture, and work with the relevant engineering teams to take new capabilities through production adoption and repeatable expansion. The design scope is exabyte-scale storage and infrastructure spanning multiple millions of CPU cores. The challenge is not simply forecasting more resources: it is making complete, workload-ready capacity repeatable, with a clear path from product requirements through architecture, deployment and validation. A data pipeline, database query, file operation or execution snapshot can affect whether a product or agent succeeds; you will connect those outcomes to the systems underneath. 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: Translate model, product and data-platform needs into precise access patterns, consistency, durability, freshness, availability and scalability requirements. Connect memory, history, retrieval and resumable work to capability and end-to-end latency. Partner with engineering to transform data and storage architecture into repeatable scale units: standardized provisioning, placement, routing, data movement and readiness checks that bring storage, compute and networking online together.

About the Team The Artifacts team is building the AI-native creation layer for documents, spreadsheets, slide decks, dashboards, reports, analyses, and new forms of interactive work products. We are rethinking what creation looks like when models can move from an ambiguous user goal to a polished, editable artifact with strong structure, taste, correctness, and speed. This is a high-agency team working across product, infrastructure, and research. We partner closely with model training teams to shape how frontier models create artifacts, and with ChatGPT product teams to turn those capabilities into experiences that millions of people can use. The work spans full-stack product engineering, model integration, rendering and editing systems, collaboration, storage, evaluation loops, and production reliability. Our ambition is to build the premier product experience for AI-generated artifacts: starting with familiar work products like slides, sheets, and docs, then expanding into new artifact types that are only possible in an AI-native world. About the Role As Engineering Manager, Artifacts, you will lead and grow the engineering team responsible for building this product and technical foundation. You will manage a team of full-stack and infrastructure-oriented engineers, set technical direction, and stay hands-on enough to shape architecture and debug hard problems. This role sits at the intersection of product engineering, research, and infrastructure. You will partner with researchers on how models are trained and evaluated for artifact creation, with product and design on the user experience. This is a strong fit for a technical manager who wants to build and ship, not only coordinate. The team has a fast trajectory, so you will help define both the product surface and the team that builds it. In this role, you will: Lead, manage, and grow a team building AI-native artifact creation experiences across documents, spreadsheets, slide decks, and emerging artifact form

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: Most of the value of owning a model shows up at serving time. We're building a platform that covers the whole life of an LLM -- train it, deploy it, observe it -- and inference is where teams feel the difference every day. We already run elastic inference, sandboxes, distributed volumes, and multi-node training, and we control the infrastructure underneath, so the serving stack is ours to shape rather than something we resell. You will do hands-on inference research at Modal, working with the research lead to pick high-impact bets and owning them end to end. The bets that matter most are the ones that move cost per token and tail latency on the workloads our customers actually run. What you'll do: Own end-to-end inference research bets: speculative decoding, disaggregated prefill/decode, quantization (FP8, INT4), KV-cache and memory management, autoscaling for spik