Senior Hardware/Production Test Software Engineer

About the TeamThe Scaling team at OpenAI forms the architectural and engineering foundation of our infrastructure. We innovate and implement advanced systems that facilitate the deployment and operation of next-generation AI models. Our responsibilities encompass system software, networking, platform architecture, fleet-level monitoring, and performance enhancement.About the RoleWe are seeking a skilled software engineer proficient in transforming early-stage, sometimes chaotic, pre-production hardware into stable, operational systems. You will be pivotal in bootstrapping, imaging, integrating with the Kubernetes control plane, and ensuring observability. Your role will bridge early hardware bring-up, provisioning automation, fleet and cluster management, and integration with lab or cloud services—effectively converting new SKUs into usable capacity for our internal stakeholders.Key ResponsibilitiesManage the comprehensive bring-up and bootstrapping process for new systems and compute nodes, transitioning from bare metal or early access in lab or production/cloud settings to schedulable fleet capacity, including image building, user-data/configuration, cluster joining, and readiness gates.Develop and uphold top-tier golden image and provisioning workflows across lab and production environments, collaborating with partner-provided base images while ensuring OS/version compatibility.Collaborate with partner teams to integrate nodes into our fleet infrastructure and Infrastructure as Code (IaC) pipelines (Terraform, Chef, etc.), guaranteeing that cloud resources align seamlessly with our internal lifecycle expectations.Work closely with scheduling and platform owners to ensure new hardware is accessible and properly scheduled, addressing pool definitions, network connectivity, routing, admission controls, and platform-specific requirements.Ensure registration and inventory accuracy, providing hands-on support to track nodes and their metadata from end to end.Partner with teams to establish baseline health and telemetry monitoring for bring-up, including critical health signals, pass/fail assessments, and automated reporting for initial ramp decisions.Troubleshoot issues across various layers, including PXE/boot-loader, UEFI/BIOS, BMC, OS bring-up, NIC/network accessibility, kubelet/control-plane connectivity, storage limitations, and early lab/rack scenarios.

Who We AreSamsara (NYSE: IOT) is at the forefront of the Connected Operations™ Cloud, a transformative platform that empowers businesses reliant on physical operations to tap into Internet of Things (IoT) data. Our aim is to provide actionable insights that enhance safety, efficiency, and sustainability across vital industries such as agriculture, construction, transportation, and manufacturing. By digitally transforming these sectors, which represent over 40% of global GDP, we are contributing to a more efficient and sustainable economy.Joining Samsara means being part of a team that is defining the future of physical operations. You will engage in cutting-edge solutions, including Video-Based Safety, Vehicle Telematics, and Equipment Monitoring, within a supportive environment that fosters innovation and long-term impact.About the Role:We are seeking a Senior Hardware Systems Engineer to enhance our rapidly expanding product line. Your primary responsibility will involve leading the electrical engineering components of product architecture and design, grounded in comprehensive feasibility, design, and cost analyses. This encompasses critical aspects such as component selection, thermal management, and antenna design. You will leverage extensive telemetry and direct customer insights to inform and refine our product designs. Collaborating closely with Product Management, Firmware, and Hardware leadership, you will influence key engineering decisions while mentoring fellow engineers. The role will also require interaction with our US and Taiwan EE teams, as well as our Supply Chain and laboratory resources, to achieve our project goals effectively.This role is hybrid, requiring you to be in our San Francisco, CA office three days a week, with the flexibility to work remotely for two days. Travel may be necessary up to 25% of the time, and proximity to an international airport is essential. We offer relocation assistance for this position and welcome candidates from across the U.S. who are willing to relocate to the Bay Area.

Join Stripe as a Staff Software Engineer in our Stream Compute team, where you will play a pivotal role in building scalable solutions that power the financial infrastructure of the internet. As a member of our innovative engineering team, you will leverage your expertise to design and implement robust software solutions that enhance the performance and reliability of our streaming data capabilities.

Physical Intelligence seeks a Hardware Systems Engineering Intern to support its core hardware team in San Francisco. This group maintains the infrastructure behind a robotic fleet that performs real-world tasks, from washing dishes for hours to brewing coffee in both warehouse and unpredictable outdoor settings. Role overview The hardware team operates at the intersection of mechanical, electrical, and systems engineering. Team members work closely with software, controls, and manufacturing engineers to transition robots from prototypes into production. Daily work includes developing and running test protocols, troubleshooting failures in the field, and building systems that ensure reliability in a range of environments. What you will do Cross-disciplinary problem solving: Address challenges that combine mechanical, electrical, and control systems. Analyze ambiguous issues, identify root causes, and design practical fixes. Reliability analysis: Collect data and conduct reliability studies to spot failure trends, monitor system uptime, and contribute to investigations using methods such as RCCA and FMEA. Failure tracking: Build failure pareto charts to highlight key failure causes and timing. Work with engineers across disciplines to monitor system performance throughout different builds and deployments. Tooling and process design: Design and construct tools, jigs, and processes that improve speed, safety, and reliability for the robot fleet. Test protocols: Execute and refine testing procedures for new hardware, field repairs, and post-service checks. Build and production support: Assist with hardware builds, inventory tracking, materials handling, and vendor coordination. Configuration and serialization: Help implement configuration, serialization, and test tracking systems to streamline service and replacement processes. Requirements Pursuing or completed a Bachelor's degree in Mechanical or Mechatronics Engineering.

About Our TeamAt OpenAI, our Hardware team is at the forefront of developing cutting-edge silicon and comprehensive system solutions tailored to the specific needs of advanced AI workloads. We pride ourselves on crafting the next generation of AI-native silicon, collaborating closely with software engineers and research teams to ensure our hardware is seamlessly integrated with AI models. Our mission extends beyond creating production-grade silicon for OpenAI’s supercomputing infrastructure; we also innovate custom design tools and methodologies that spark innovation and enable hardware specifically optimized for AI.About the RoleAs a Software Engineer on the Scaling team, you will play a pivotal role in designing and optimizing the foundational stack that manages computation and data flow across OpenAI’s supercomputing clusters. Your responsibilities will include crafting high-performance runtimes, developing custom kernels, enhancing compiler infrastructure, and building scalable simulation systems to validate and optimize distributed training workloads.This position requires you to work at the intersection of systems programming, machine learning infrastructure, and high-performance computing, where you will create intuitive developer APIs alongside highly efficient runtime systems. You will balance usability and introspection with the imperative for stability and performance across our dynamic hardware landscape.This role is based in San Francisco, CA, featuring a hybrid work model (three days in-office per week). Relocation assistance is provided.Key Responsibilities:Design and implement APIs and runtime components to efficiently manage computation and data movement for diverse ML workloads.Enhance compiler infrastructure by developing optimizations and compiler passes to accommodate evolving hardware advancements.Engineer and refine compute and data kernels, ensuring precision, high performance, and compatibility across simulation and production settings.Analyze and optimize system bottlenecks, focusing on I/O, memory hierarchy, and interconnects at both local and distributed scales.Create simulation infrastructure to validate runtime behaviors, test modifications to the training stack, and support the early development of hardware and systems.Quickly deploy updates to runtime and compiler across new supercomputing builds in close collaboration with hardware and research teams.Work across a varied tech stack, primarily utilizing Rust and Python, with a chance to influence architectural decisions within the training framework.

Team and Platform Focus The Compute Infrastructure team at OpenAI designs, builds, and maintains the systems that support AI research at scale. This work brings together accelerators, CPUs, networking, storage, data centers, orchestration software, agent infrastructure, developer tools, and observability. The aim is to create a reliable, unified experience for researchers and product teams across the company. Projects span the full stack: capacity planning, cluster lifecycle management, bare-metal automation, and distributed systems. The team manages Kubernetes scheduling, system optimization, high-performance networking, storage, fleet health, reliability, workload profiling, benchmarking, and improvements to the developer experience. Even small improvements in communication, scheduling, hardware efficiency, or debugging can significantly accelerate research. OpenAI matches engineers to areas within Compute Infrastructure that align with their skills and interests. Role Overview This Software Engineer role centers on building and evolving the compute platform that supports OpenAI’s research and products. Candidates may bring expertise in low-level systems, high-performance computing, distributed infrastructure, reliability, CaaS, agent infrastructure, developer platforms, tooling, or infrastructure user experience. The most important qualities are strong analytical skills, the ability to write resilient code, and a collaborative approach that helps colleagues move faster and with more confidence. What You Will Work On Working close to hardware or at the user interaction layer Developing CaaS and agent infrastructure Managing control and data planes that connect the system Bringing new supercomputing capabilities online Optimizing training workloads through profiler traces and benchmarks Improving NCCL and collective communication Analyzing GPUs, NICs, topology, firmware, thermal dynamics, and failure modes Designing abstractions to unify diverse clusters into a single platform Areas of Expertise No one is expected to cover every area listed. Some engineers focus on system performance, kernel or runtime behavior, large-scale networking protocols, RDMA, NCCL, GPU hardware, benchmarking, scheduling, or hardware reliability. Others improve the platform’s usability through APIs, tools, workflows, and developer experience. The team values strong engineering judgment and a drive to advance the field.

About Our TeamAt OpenAI, our Hardware organization is at the forefront of developing cutting-edge silicon and system-level solutions tailored for the specific demands of advanced AI workloads. Our team is dedicated to creating the next generation of AI-native silicon, collaborating closely with software and research partners to co-design hardware that is seamlessly integrated with AI models. We not only deliver production-grade silicon for OpenAI’s supercomputing infrastructure but also innovate custom design tools and methodologies that drive acceleration and optimization specific to AI.About This RoleAs a member of our hardware optimization and co-design team, you will play a crucial role in co-designing future hardware from various vendors, focusing on programmability and high performance. You will partner with our kernel, compiler, and machine learning engineers to comprehend their distinct requirements concerning ML techniques, algorithms, numerical approximations, programming expressivity, and compiler optimizations. Your advocacy for these constraints will help shape and influence future hardware architectures aimed at efficient training and inference for our models. If you are passionate about efficiently distributing large language models across devices, optimizing system-wide networking bottlenecks, and customizing the compute pipeline and memory hierarchy of hardware platforms while simulating workloads at various abstraction levels, then this opportunity is perfect for you!This position is based in San Francisco, CA, utilizing a hybrid work model of three days in the office each week, with relocation assistance available for new hires.Key Responsibilities:Collaborate on the co-design of future hardware focusing on programmability and performance with hardware vendors.Support hardware vendors in developing optimal kernels and integrating support within our compiler.Generate performance estimates for critical kernels across diverse hardware configurations, influencing decisions regarding compute core and memory hierarchy features.Create system performance models at various abstraction levels and conduct analyses to guide decisions on scaling and front-end networking.Engage with machine learning engineers, kernel engineers, and compiler developers to align on high-performance accelerator needs.Facilitate communication and coordination with internal and external partners.Shape the roadmap for hardware partners to optimize their products for our AI capabilities.

At Crusoe, our mission is to propel the availability of energy and intelligence. We are designing the engine that fuels a future where individuals can ambitiously innovate with AI, all while upholding standards of scale, speed, and sustainability.Join us in the AI revolution powered by sustainable technology at Crusoe. Here, you will spearhead significant innovations, make a lasting impact, and collaborate with a team that is leading the charge in responsible, transformative cloud infrastructure.About This Role:We are on the lookout for a Hardware Production / Sustaining Engineer to enhance Crusoe’s Hardware Systems Engineering team and address critical skill gaps in debugging, validation, and production support of high-performance computing systems. In this role, you will oversee the entire hardware lifecycle—from prototype initiation to mass production—while driving automation, resolving intricate issues, and ensuring reliability across Crusoe Cloud’s GPU- and CPU-based infrastructure.You will collaborate closely with cross-functional teams to support, debug, and optimize hardware platforms at scale, with a specific focus on PCIe, InfiniBand, and NVMe/storage, which are recognized as vital areas for enhanced expertise. Your contributions will significantly influence Crusoe’s capability to deploy and manage sustainable, AI-first computing systems that deliver world-class performance and reliability.What You’ll Be Working On:Lead the entire hardware development and sustaining lifecycle, encompassing feasibility, bring-up, validation, deployment, and ongoing production support.Create and maintain scripting and automation frameworks for hardware testing, diagnostics, and continuous reliability enhancements.Guide deep troubleshooting and debugging across:PCIe (link training, topology, performance issues)InfiniBand (fabric debugging, throughput, connectivity issues)NVMe/storage (performance bottlenecks, firmware interactions, failure analysis)Perform thorough system validation and characterization for GPU, CPU, and high-performance computing platforms.Assist in end-to-end integration and solution testing to guarantee that Crusoe Cloud products fulfill performance, reliability, and scalability standards.Work in tandem with mechanical, thermal, firmware, software, and manufacturing teams to resolve system-level challenges.

About Our TeamAt OpenAI, our Hardware team specializes in developing cutting-edge silicon and system-level solutions tailored to meet the rigorous demands of advanced AI applications. We are at the forefront of creating the next generation of AI-native silicon and collaborate closely with our software and research partners to ensure our hardware is seamlessly integrated with AI models. Our mission extends beyond just delivering production-grade silicon for OpenAI’s supercomputing infrastructure; we are also dedicated to innovating custom design tools and methodologies that enhance hardware optimized for AI.About the PositionWe are seeking a highly skilled Mechanical Engineer with a minimum of 7 years of experience in the design of IT hardware, encompassing everything from chip/package to system levels. In this role, you will collaborate with a team of experts across thermal, mechanical, electrical, software, and systems engineering to support the design, analysis, and validation of mechanical and thermal systems that guarantee the reliability, efficiency, and longevity of critical hardware. A strong analytical mindset, hands-on testing experience, and the ability to thrive in a fast-paced, multidisciplinary environment are essential for success in this role.This position is based in San Francisco, CA, and follows a hybrid work model, requiring 3 days in the office per week. We also offer relocation assistance for new hires.Key ResponsibilitiesLead mechanical designs for AI supercomputer products within data center applications.Collaborate with cross-functional teams to design and enhance thermal solutions for data center hardware, including chips, power modules, and system-level cooling architectures.Integrate thermal management strategies into hardware designs from concept through to mass production.Design and validate mechanical systems such as chassis, enclosures, and cooling systems while ensuring compliance with performance and reliability standards.Conduct 3D modeling, finite element analysis (FEA), tolerance analysis, and prototyping to ensure manufacturability and adherence to stringent quality requirements.Perform mechanical testing, including vibration, shock, and thermal cycling, to ensure long-term reliability under extreme operating conditions.Identify and assess new technologies and methodologies to enhance mechanical and thermal performance in product designs, contributing expertise in mechanical design to new product development initiatives.

Join our innovative team at fal as a Staff Software Engineer specializing in large-scale computation platforms. We are seeking a seasoned software engineer with extensive experience in developing backend systems that efficiently orchestrate workloads and manage resource constraints. Your expertise in foundational cloud infrastructure and Linux provisioning will be crucial as you work towards achieving high reliability and scalability with minimal operational overhead.

Why Join Flux?At Flux, we are revolutionizing hardware development by creating the world's first AI Hardware Engineer. Our mission is to democratize access to cutting-edge hardware technology and transform how electronics are conceived and manufactured globally.Role OverviewAs a Software Engineer focusing on Agentic Development, you will be integral in building the core intelligence of our platform. You will develop innovative workflows, reasoning graphs, and seamless integrations that empower both novice users to transform ideas into manufacturable hardware and experienced electrical engineers to learn from past production challenges.Your role will uniquely merge web engineering with AI system design, utilizing TypeScript and LangGraph to embed smart functionalities directly into our design environment.Key ResponsibilitiesCraft agentic reasoning capabilities using TypeScript (LangGraph).Incorporate AI functionalities into the Flux web application (React/Redux) and Chat UI.Implement telemetry and logging systems to monitor runtime health, performance, and cost efficiency.Collaborate with product and electrical engineers to enhance intelligent ECAD workflows.Design and evaluate experiments; convert insights into actionable engineering decisions.Contribute to the development of agentic patterns, conventions, and best practices across the engineering organization.

Lumafield develops X-Ray CT scanners designed to make advanced imaging more accessible and affordable. The company’s cloud software provides engineers with detailed visualization tools, helping them analyze complex products and make informed decisions. Role overview This full-time, on-site Hardware Systems Engineer position is based in San Francisco. The role centers on leading hardware development for industrial CT scanners. Collaboration with researchers and designers is a key part of the job, with a focus on improving product development for a range of industries. What you will do Lead hardware systems development for industrial CT scanners Design and manage electrical architecture Develop firmware and oversee system integration Work hands-on to transform concepts into working products Collaborate with cross-functional teams to address customer needs Team and collaboration The engineering team includes experienced researchers and designers who value curiosity and rigor. The group is impact-driven and backed by leading venture capital firms. Location This role requires working on-site at Lumafield’s San Francisco office.

Join Astranis as a Senior Software Engineer specializing in Hardware Testing, where you'll play a crucial role in developing and enhancing our cutting-edge satellite technology. You will work alongside a talented team focused on creating reliable and innovative hardware solutions that redefine connectivity globally.Your expertise will contribute to our mission of delivering affordable internet access to underserved regions, making a real difference in people's lives. If you are passionate about technology and eager to tackle challenging problems, this opportunity is perfect for you!

At Crusoe, our mission is to drive the evolution of energy and intelligence. We are developing the technology that fuels a future where individuals can ambitiously harness AI capabilities without compromising on scale, speed, or sustainability.Join us in revolutionizing AI with sustainable solutions at Crusoe. In this role, you will be at the forefront of innovation, making a significant impact while collaborating with a team that is shaping the future of responsible and transformative cloud infrastructure.About This Role:We are looking for a dedicated Hardware Production/Sustaining Engineer to enhance Crusoe's Hardware Systems Engineering team. This position is critical for bridging essential skill gaps in debugging, validation, and production support for high-performance computing systems. You will manage the entire hardware lifecycle—from prototype initiation to large-scale production—focusing on automation, deep troubleshooting, and reliability within Crusoe Cloud’s GPU- and CPU-oriented infrastructure.Your collaboration with cross-functional teams will be vital in supporting, debugging, and enhancing hardware platforms on a large scale, specifically targeting PCIe, InfiniBand, and NVMe/storage, which have been highlighted as key areas for expanded expertise. Your contributions will directly influence Crusoe’s capability to deploy and maintain sustainable, AI-driven computing systems that deliver exceptional performance and reliability.Your Responsibilities Will Include:Leading the complete hardware development and sustaining lifecycle, encompassing feasibility studies, bring-up, validation, deployment, and ongoing production support.Creating and sustaining automation frameworks and scripts for hardware testing, diagnostics, and continual reliability enhancements.Executing in-depth troubleshooting and debugging across:PCIe (including link training, topology, and performance issues)InfiniBand (focusing on fabric debugging, throughput, and connectivity challenges)NVMe/storage (addressing performance bottlenecks, firmware interactions, and failure analyses)Performing extensive system validation and characterization for GPU, CPU, and high-performance computing platforms.Assisting in end-to-end integration and solution testing to guarantee that Crusoe Cloud products fulfill performance, reliability, and scalability standards.Collaborating with teams across mechanical, thermal, firmware, software, and manufacturing domains to troubleshoot and enhance system performance.

About EventualAt Eventual, we believe that every innovative AI application—from foundational models to self-driving vehicles—demands the ability to process vast amounts of images, video, and intricate data. Unfortunately, existing data platforms, such as Databricks and Snowflake, are designed for traditional spreadsheet-like analytics, not for the petabytes of multimodal data that truly drive AI advancements. This limitation leads teams to spend excessive time on fragile infrastructure, diverting them from essential research and product development.Founded in 2022, Eventual's mission is to revolutionize data querying, making it as intuitive as working with tables and robust enough to support production workloads. Our open-source engine, Daft, is specifically engineered for real-world AI systems. It effectively coordinates with external APIs, manages GPU clusters, and addresses failures that conventional engines cannot handle. Major companies like Amazon, Mobileye, Together AI, and CloudKitchens are already leveraging Daft for their critical workloads.Our team is composed of industry veterans from Databricks, AWS, Nvidia, Pinecone, GitHub Copilot, Tesla, and beyond, and we've quadrupled our size within just a year. With Series A and seed funding from notable investors including Felicis, CRV, Microsoft M12, Citi, Essence, Y Combinator, Caffeinated Capital, Array.vc, and prominent angel investors from the co-founders of Databricks and Perplexity, we are actively expanding our team. Join us—Eventual is only at the beginning of its journey.We are currently seeking passionate individuals to join our tight-knit team, who will work together in our San Francisco Mission district office four days a week.

At Rylo, we are revolutionizing the way you capture and share your experiences. Our state-of-the-art camera is designed to record your surroundings with breathtaking clarity and stability, eliminating the hassle of traditional video capture. Created by a team of visionary engineers from Instagram and Apple, our innovative stabilization software and user-friendly smartphone app ensure that every shot you take is a masterpiece. With Rylo, you can focus on enjoying the moment while we handle the technicalities of creating stunning videos.Experience Rylo in actionAs a Software Engineer specializing in Computational Photography, you will play a crucial role in enhancing the core algorithms that power the Rylo camera and future products. Your work will fundamentally enhance the photography and cinematography experience, focusing on improving image quality and developing groundbreaking computational photography features. You will engage in the complete lifecycle of algorithm development, from design and implementation to quality evaluation and performance optimization, culminating in successful deployment.Your collaboration with software engineers, hardware engineers, and designers will allow you to push the boundaries of consumer camera technology.

About Our TeamAt OpenAI, our Storage Infrastructure team is at the forefront of enabling data accessibility, placement, and lifecycle management through advanced APIs. We prioritize scalability, reliability, security, and usability to meet the demands of our pioneering AI research.Role OverviewWe are seeking a talented Software Engineer to join our Storage Infrastructure team, where you will architect and maintain Exascale systems designed to efficiently and reliably manage research data across multiple regions.The ideal candidate will have extensive experience in distributed systems, particularly in developing exascale data management solutions or distributed filesystems.Your ResponsibilitiesDesign and develop software solutions to manage exascale data, ensuring accessibility for researchers.Enhance the reliability, predictability, and cost efficiency of our storage systems.Collaborate with researchers to understand and address diverse data use cases.Implement robust security measures to protect our critical datasets.Ideal Candidate ProfileStrong foundation in distributed systems principles with a proven ability to design and implement scalable, reliable, and secure storage architectures.Proficiency in programming languages relevant to storage systems development.Experience with cloud platforms, particularly Azure.Familiarity with AI/ML data access patterns.A proactive approach and adaptability in a fast-paced, dynamic environment.About OpenAIOpenAI is a cutting-edge AI research and deployment organization committed to ensuring that general-purpose artificial intelligence benefits all of humanity. We strive to push the boundaries of AI capabilities while ensuring safety and human-centric development. Our mission is to encompass and appreciate diverse perspectives, voices, and experiences that reflect the full spectrum of humanity.We are proud to be an equal opportunity employer, committed to fostering an inclusive workplace where all individuals are respected and valued.

Databricks is looking for a Senior Software Engineer focused on Compute Infrastructure in San Francisco, California. This position centers on building and improving compute architecture to support greater performance and scalability across Databricks' platform. What you will do Develop and optimize compute infrastructure to handle demanding data processing and analytics workloads. Work closely with teams from different disciplines to deliver reliable, high-quality solutions for customers. Impact Your contributions will help define how data processing and analytics evolve at Databricks. The work directly supports customers’ ability to scale and perform complex tasks in the cloud. Who we’re looking for Strong background in cloud technologies and compute systems. Enjoys tackling complex technical challenges. Collaborative approach to problem-solving with cross-functional teams.

At sfcompute, we are on a mission to revolutionize the infrastructure landscape by minimizing the risks associated with the largest build-outs in history.When financing GPU clusters and the data centers that support them, having a contract in place—what we call an "offtake"—is crucial. This ensures that customers have signed on to lease the cluster even before it’s constructed.The financing process for GPU clusters carries inherent risks due to thin margins and large volumes. Lenders often hesitate to take on the risk that developers may default on their loans, while developers are wary of being unable to sell their clusters. This dynamic leads to the necessity of transferring risk to customers via fixed-price, long-term contracts.If customer risk isn't effectively mitigated, a market bubble can form. Unlike traditional SaaS models, application layer companies engage in multi-year contracts for compute and inference while offering customers monthly subscriptions. A miscalculation in purchasing can spell disaster; a small change in revenue growth could lead to profits or bankruptcy. Imagine a world where companies could exit their contracts by selling them back to the market.As AI technology scales, compute power will increasingly only be available for those who can manage the associated risks. A small startup in a San Francisco Victorian house cannot feasibly commit to a 5-year, take-or-pay contract for $100 million supercomputers, but they might be able to purchase a month of liquidity that someone else has sold back.That’s the market we’re building: a liquid marketplace for GPU offtake.About the RoleAs part of our infrastructure team, you will help design and deploy some of the most powerful GPU clusters in existence, with even smaller clusters today having ranked in the TOP500 five years ago. Your responsibilities will include participating in on-call rotations, deploying new environments, troubleshooting issues, and embracing automation to facilitate large-scale deployments. As a member of a small but dynamic team, you'll have the opportunity to significantly influence our company culture, mentor junior engineers, and engage directly with our customers.