About the Role Together AI runs one of the largest GPU fleets in the world. The Infra Agent Systems team builds the software systems that power and automate that infrastructure. We develop production AI agents that diagnose hardware failures, investigate incidents, correlate signals across the fleet, and automate operational workflows. Alongside these agents, we build the platform they run on, including knowledge graphs, retrieval systems, orchestration frameworks, and developer tooling. You’ll work across two areas: Infrastructure Agent Systems — Build production AI agents that help operate our GPU fleet by diagnosing failures, investigating incidents, gathering evidence from live systems, and assisting with remediation. These agents are used every day by our infrastructure and datacenter teams through APIs, CLI, dashboards, and Slack. Core Agent Platform — Build the platform that powers these agents, including knowledge graphs, search and retrieval, orchestration, evaluation, and the tooling that enables agents to reason, act, and continuously improve. We’re working on something that hasn’t really been done before: building knowledge graphs and self-improving AI agents that understand, operate, and continuously improve large-scale AI infrastructure. This is an opportunity to work at the intersection of AI agents, distributed systems, infrastructure, and automation , solving challenging engineering problems with real production impact. There’s an enormous amount to build, learn, and shape as we define the future of autonomous infrastructure. responsible for delivering the software but also for operating and supporting it in production. Why this Role You’ll work on two hard problems at the same time: making AI agents trustworthy enough to operate production infrastructure, and building the knowledge, retrieval, and distributed systems that make those agents effective. You’ll have the opportunity to build foundational systems from the ground up, work on infrastructur
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About the Role Together AI runs one of the largest GPU fleets in the world. The Infra Agent Systems team builds the software systems that power and automate that infrastructure. We develop production AI agents that diagnose hardware failures, investigate incidents, correlate signals across the fleet, and automate operational workflows. Alongside these agents, we build the platform they run on, including knowledge graphs, retrieval systems, orchestration frameworks, and developer tooling. You’ll work across two areas: Infrastructure Agent Systems — Build production AI agents that help operate our GPU fleet by diagnosing failures, investigating incidents, gathering evidence from live systems, and assisting with remediation. These agents are used every day by our infrastructure and datacenter teams through APIs, CLI, dashboards, and Slack. Core Agent Platform — Build the platform that powers these agents, including knowledge graphs, search and retrieval, orchestration, evaluation, and the tooling that enables agents to reason, act, and continuously improve. We’re working on something that hasn’t really been done before: building knowledge graphs and self-improving AI agents that understand, operate, and continuously improve large-scale AI infrastructure. This is an opportunity to work at the intersection of AI agents, distributed systems, infrastructure, and automation , solving challenging engineering problems with real production impact. There’s an enormous amount to build, learn, and shape as we define the future of autonomous infrastructure. responsible for delivering the software but also for operating and supporting it in production. Why this Role You’ll work on two hard problems at the same time: making AI agents trustworthy enough to operate production infrastructure, and building the knowledge, retrieval, and distributed systems that make those agents effective. You’ll have the opportunity to build foundational systems from the ground up, work on infrastructur
As a Staff Engineer on Datadog's Compute – Disruption and Workload Placement team, you'll help define how our Kubernetes fleet scales to meet the demands of rapidly growing AI and cloud-native workloads. You'll work on the systems that ensure engineering teams have the right compute capacity, in the right region, at the right time across AWS, Google Cloud, and Azure. This is a highly technical, high-impact role where you'll shape the future of capacity orchestration, influence platform architecture, and solve infrastructure challenges that directly support Datadog's continued growth. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Lead the technical direction of capacity management and workload placement for Datadog's Kubernetes platform spanning 100,000+ virtual machines across multiple cloud providers. Design and build systems that optimize how engineering workloads are scheduled and deployed across regions while balancing capacity constraints, reliability, and performance. Partner across infrastructure teams to evolve multi-region and multi-cloud capacity orchestration as Datadog continues to scale. Develop production software in Go to improve Kubernetes platform capabilities, automation, and operational efficiency. Use data and capacity signals to influence infrastructure decisions, forecast growth, and improve workload placement strategies. Who You Are: You have significant experience designing and operating large-scale Kubernetes-based infrastructure or platform systems. You are an experienced software engineer with strong programming skills, ideally in Go or a comparable systems programming language. You have hands-on experience with at least one major cloud provider (AWS, Google Cloud, or Azure) and understand distributed cloud infrastructure. Yo
As a Staff Engineer on Datadog's Compute – Disruption and Workload Placement team, you'll help define how our Kubernetes fleet scales to meet the demands of rapidly growing AI and cloud-native workloads. You'll work on the systems that ensure engineering teams have the right compute capacity, in the right region, at the right time across AWS, Google Cloud, and Azure. This is a highly technical, high-impact role where you'll shape the future of capacity orchestration, influence platform architecture, and solve infrastructure challenges that directly support Datadog's continued growth. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Lead the technical direction of capacity management and workload placement for Datadog's Kubernetes platform spanning 100,000+ virtual machines across multiple cloud providers. Design and build systems that optimize how engineering workloads are scheduled and deployed across regions while balancing capacity constraints, reliability, and performance. Partner across infrastructure teams to evolve multi-region and multi-cloud capacity orchestration as Datadog continues to scale. Develop production software in Go to improve Kubernetes platform capabilities, automation, and operational efficiency. Use data and capacity signals to influence infrastructure decisions, forecast growth, and improve workload placement strategies. Who You Are: You have significant experience designing and operating large-scale Kubernetes-based infrastructure or platform systems. You are an experienced software engineer with strong programming skills, ideally in Go or a comparable systems programming language. You have hands-on experience with at least one major cloud provider (AWS, Google Cloud, or Azure) and understand distributed cloud infrastructure. Yo
Location : Come and join us either in Berlin or Hamburg! Freenow by Lyft empowers smarter mobility decisions helping people to move freely and cities to thrive. One of our core goals for 2026 is the complete digitalization of the European taxi market. We are partnering with local fleets to provide them with our advanced Dispatch and Fleet Management software completely for free, helping them cut costs, defend against ride-hailing giants, and thrive. We are looking for an empathetic, relentless, and hands-on Sales Manager to be the face of this initiative! YOUR DAILY ADVENTURES WILL INCLUDE: Prospect, engage, travel and pitch our Dispatch tool to SMB taxi companies. You will be the primary catalyst for transitioning legacy fleets into modern, connected partners Guide fleet owners and head dispatchers through the fear of operational change Act as the voice of our partners. You will gather on-the-ground feedback about our software and collaborate directly with our Product and Strategy teams to help "co-build" the ultimate solution TO BE SUCCESSFUL IN THIS ROLE: 3-5 years in B2B Business Development, Sales, Account Executive roles. Backgrounds in mobility, logistics, or selling SaaS to SMBs are highly preferred Proven track record of managing a B2B pipeline and handling objections. You understand that even when a product is free, you still have to expertly "sell" the time, effort, and operational shift required to adopt it Strong communication skills with the ability to build trust and long-term relationships Ability to deeply understand how a partner's business operates on a procedural level. You are adept at guiding new partners step-by-step through the transition, ensuring they smoothly adopt new software and daily routines You view travel not as a chore, but as an essential part of the job. You are comfortable being on the road for a significant portion of your time (up to 40-50%) to meet partners exactly where they operate Fluency in German and English is required
Location : Come and join us either in Berlin or Hamburg! Freenow by Lyft empowers smarter mobility decisions helping people to move freely and cities to thrive. One of our core goals for 2026 is the complete digitalization of the European taxi market. We are partnering with local fleets to provide them with our advanced Dispatch and Fleet Management software completely for free, helping them cut costs, defend against ride-hailing giants, and thrive. We are looking for an empathetic, relentless, and hands-on Sales Manager to be the face of this initiative! YOUR DAILY ADVENTURES WILL INCLUDE: Prospect, engage, travel and pitch our Dispatch tool to SMB taxi companies. You will be the primary catalyst for transitioning legacy fleets into modern, connected partners Guide fleet owners and head dispatchers through the fear of operational change Act as the voice of our partners. You will gather on-the-ground feedback about our software and collaborate directly with our Product and Strategy teams to help "co-build" the ultimate solution TO BE SUCCESSFUL IN THIS ROLE: 3-5 years in B2B Business Development, Sales, Account Executive roles. Backgrounds in mobility, logistics, or selling SaaS to SMBs are highly preferred Proven track record of managing a B2B pipeline and handling objections. You understand that even when a product is free, you still have to expertly "sell" the time, effort, and operational shift required to adopt it Strong communication skills with the ability to build trust and long-term relationships Ability to deeply understand how a partner's business operates on a procedural level. You are adept at guiding new partners step-by-step through the transition, ensuring they smoothly adopt new software and daily routines You view travel not as a chore, but as an essential part of the job. You are comfortable being on the road for a significant portion of your time (up to 40-50%) to meet partners exactly where they operate Fluency in German and English is required
Location : Come and join us either in Berlin or Hamburg! Freenow by Lyft empowers smarter mobility decisions helping people to move freely and cities to thrive. One of our core goals for 2026 is the complete digitalization of the European taxi market. We are partnering with local fleets to provide them with our advanced Dispatch and Fleet Management software completely for free, helping them cut costs, defend against ride-hailing giants, and thrive. We are looking for an empathetic, relentless, and hands-on Sales Manager to be the face of this initiative! YOUR DAILY ADVENTURES WILL INCLUDE: Prospect, engage, travel and pitch our Dispatch tool to SMB taxi companies. You will be the primary catalyst for transitioning legacy fleets into modern, connected partners Guide fleet owners and head dispatchers through the fear of operational change Act as the voice of our partners. You will gather on-the-ground feedback about our software and collaborate directly with our Product and Strategy teams to help "co-build" the ultimate solution TO BE SUCCESSFUL IN THIS ROLE: 3-5 years in B2B Business Development, Sales, Account Executive roles. Backgrounds in mobility, logistics, or selling SaaS to SMBs are highly preferred Proven track record of managing a B2B pipeline and handling objections. You understand that even when a product is free, you still have to expertly "sell" the time, effort, and operational shift required to adopt it Strong communication skills with the ability to build trust and long-term relationships Ability to deeply understand how a partner's business operates on a procedural level. You are adept at guiding new partners step-by-step through the transition, ensuring they smoothly adopt new software and daily routines You view travel not as a chore, but as an essential part of the job. You are comfortable being on the road for a significant portion of your time (up to 40-50%) to meet partners exactly where they operate Fluency in German and English is required
About the Team The ChatGPT Model Flywheel team unified goal is to transform model advancements into great ChatGPT user experiences through reliable serving, rapid experimentation, safe deployment, and continuous improvement. Team Focus Areas Model Experimentation: Enable rapid, safe model validation for ChatGPT and Codex products through experiment automation and lifecycle management. Model Deployment: Ensure safe, scalable deployment of model capabilities with robust rollout and operational tooling. Automate capacity management and incorporate platform-wide health monitors. Model Measurement: Build comprehensive evaluation and measurement systems for model quality, from user signals to launch scorecards. Improve end-to-end feedback loops for continual model improvement. Key Partnerships Collaborate cross-functionally with teams including Model Measurement DS, Research, Codex, Fleet, Inference, and API. In this role, you will: Elevate and consolidate ChatGPT’s harness, context management, and system prompt frameworks. Drive expansion and improvement of multi-tier model experiences. Support and scale self-serve experiment capabilities and automated guardrails. Lead model rollout automation, capacity management, and health monitoring. Shape end-to-end measurement systems (evals, grader signals, user feedback, etc.). You might thrive in this role if you have: Proven experience leading engineering teams in complex, cross-functional environments. Demonstrated success shipping production systems at scale (ideally for AI or large backend services). Deep understanding of model-driven product development, deployment lifecycle, and measurement tooling. Excellent communication and collaboration skills—experience interfacing directly with engineering, research, and product stakeholders. Prior involvement with large language models, distributed infrastructure, or experimentation platforms is a plus. Why Work With Us Tackle highly impactful technical challenges at the cutting edg
GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. Summary: Lead the Switchboard team, which owns the Tenant management product for Dedicated environments. This team is diverse in skills (Frontend, Backend and Reliability engineers) and owns the product end to end. The product enables self-service and workflow automations for customers and internal operators of our large scale Dedicated tenant fleet. Key Responsibilities: Lead the fullstack Switchboard team responsible for GitLab Dedicated’s customer-facing control panel, and set clear direction for how the team delivers and evolves that product. There is a strong coordination with the assigned Product Manager. Hire and develop a
What you’ll do Design and implement secure cloud pipelines that ingest very large scan datasets (multi-terabyte), reliably and resumably. Build orchestration for GPU-accelerated reconstruction and analysis with strong retry semantics, idempotency, and cost controls. Define end-to-end data lifecycle for medical imaging: raw vs intermediate vs derived artifacts, retention policies, and reproducibility. Implement security + compliance primitives appropriate for HIPAA/PHI: encryption in transit/at rest, key management, least privilege, audit logs, and access reviews. Build operational tooling: monitoring, alerting, runbooks, and incident-driven improvements for a growing device fleet. What we’re looking for Strong experience with cloud batch/queueing/orchestration, storage systems, and data pipeline reliability. Experience shipping production systems that handle large data volumes and failure-prone networks. Practical security mindset (least privilege, secrets, audit logging) and comfort operating in compliance-constrained environments. Useful experience Building reliable data pipelines at scale (queues/orchestration, resumable uploads, GPU batch execution) with strong observability. Security + privacy by default: encryption, least-privilege access, auditing, and practical HIPAA/PHI guardrails. Owning the “boring” backend details that keep a lean team moving: schemas/migrations, cost controls, retries, and runbooks. Understanding compute tradeoffs across hardware options, and specifying appropriate cloud resources.
Sr Software Engineer - Distributed Systems Engineer, EDA Infrastructure NVIDIA is hiring engineers to build and scale the infrastructure that supports our Electronic Design Automation (EDA) workloads. We are looking for engineers with strong programming skills, a deep understanding of distributed systems, experience operating large-scale production infrastructure, and excellent communication and planning abilities. You will help design reliable automation and platform services that manage large fleets of GPU-based and CPU-based compute systems used by engineering teams across NVIDIA. The ideal candidate is comfortable working across software, operating systems, cluster schedulers, networking, storage, and physical hardware. You should enjoy solving complex operational problems, eliminating repetitive work through automation, and building systems that remain reliable as infrastructure grows. If you are creative, pragmatic, and motivated to improve how critical engineering workloads are delivered, we would like to hear from you. What You Will Be Doing: Design and build platforms that automate the provisioning, configuration, operation, and lifecycle management of large-scale GPU and CPU compute infrastructure. Develop monitoring, health-management, and remediation systems that improve the reliability, availability, and utilization of EDA compute environments. Automate hardware deployment, operating-system configuration, firmware and software updates, cluster enrollment, and recovery workflows. Build reliable services and workflows that integrate with workload schedulers, infrastructure management systems, and observability platforms. Use hardware diagnostics, operating-system signals, scheduler data, and network and storage telemetry to identify
Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE As a Sr. Solution Architect you will own the product definition, technical guardrails, and lifecycle strategy for the hardware components and high-performance networking fabrics powering Everpure’s FlashArray and FlashBlade platforms. Partnering closely with Engineering, Supply Chain, and Field leadership, you will convert complex compute , chassis, and interconnect innovations into scalable, resilient platform capabilities. By defining reference architectures and validating real-world system performance, you will directly drive the commercial readiness, cost efficiency, and operational excellence of our flagship storage portfolio. WHAT YOU'll DO Subsystem Lifecycle & Roadmap Ownership : Define and drive product requirements, qualification criteria, and multi-year lifecycle roadmaps for FlashArray and FlashBlade hardware subsystems ( compute , chassis, interconnect) and networking fabrics (Ethernet, Fibre Channel, NVMe-oF) to maximize fleet reliability and performance. Architectural Guardrails & Standardization : Establish technical guardrails and reference architectures that guide Engineering, Manufacturing, and Field teams in making consistent, cost-effective hardware decisions across all product lines. Hands-On Technical Validation : Act as the technical authority for subsystem behavior by validating configurations, characterizing performance metrics, and resolving complex architectural trade-off
About Us: Sauce Labs is the leading provider of continuous test and error reporting solutions that give companies the confidence to develop, deliver and update high quality software at speed. The Sauce Labs Continuous Testing Cloud identifies quality signals in development and production, accelerating the ability to release and update web and mobile applications that look, function and perform exactly as they should on every browser, operating system and device, every single time. Sauce Labs is a privately held company funded by TPG and Riverwood Capital. The Role: Sauce Labs seeks a Senior Software Engineer to join the Virtual Device Cloud team, which builds and operates the infrastructure that hosts remote iOS, macOS, Windows, and Linux devices at scale for automated app and browser testing. This is not a narrow specialist role. We need someone who can move across the whole stack of a distributed system: understand how the pieces fit together, make the system observable enough that we know what's working and can diagnose what isn't, write and structure code with clear boundaries and the right things encapsulated, and be just as comfortable SSHing into a fleet machine to dig into a live problem as designing the system on a whiteboard. You'll join the Virtual Device Cloud team, which has deep, concentrated strength in macOS, CoreSimulator and APFS internals, and work closely with the Product Manager and with the Test Orchestration and Cloud teams. Your job is to improve testing discipline and cross-platform observability, and to raise delivery cadence, correctness, and visibility across the fleet. Responsibilities: Lead by example - set the team’s standard for testing, observability and delivery through code review and pairing, and bring others along. Own the device lifecycle - design and build the services this team owns across the whole device lifecycle, from the image a device boots to its teardown. That covers readiness, session lifecycle and the fle
Location Details: Pune, India At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely. This is a hybrid position. You’ll divide your time between working remotely from your home and an office, so you should live within commuting distance. Hybrid teams may work in-office as much as a few times a week or as little as once a month or quarter, as decided by leadership. The hiring manager can share more about what hybrid work might look like for this team. Join our Team The Linux Database Services team is responsible for operating GoDaddy's on-premise database infrastructure, supporting Percona MySQL, PostgreSQL, and Cassandra. We provide database services for internal applications and support much of GoDaddy's hosting infrastructure. Our scale is significant: thousands of database instances hosting hundreds of thousands to millions of individual databases! We are a globally distributed team with members across the EU, North America, South America, and South Asia (India), and we are growing our presence in Pune. As a Site Reliability Engineer, you will play a key role in keeping our database fleet healthy, performant, and observable. You will work across Percona MySQL, PostgreSQL, and Cassandra environments, handling both day-to-day operational work and longer-term engineering improvements. This role is ideal for someone who is passionate about building reliable, scalable infrastructure, enjoys solving complex operational challenges, and thrives in an environment where automation and continuous improvement are core to how work gets done. What you'll get to do... Maintain and improve the health of database servers and instances across a large-scale fleet Build and enhance telemetry and observability for databases and hosts Identify and implement performance improvements across database systems Execute an
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 ship AI products. THE ROLE As a Global Capacity Manager at Baseten, you will lead the "engine room" of the company, architecting, securing, and optimizing the global GPU fleet that powers our customers' AI workloads. You’ll own the end-to-end journey of capacity management, from securing multi-million dollar GPU clusters to building the automation that ensures 99.9% uptime across multi-cloud environments. This role is a great fit for entrepreneurial engineers who want to bridge the gap between high-finance asset management and deep infrastructure engineering. You will act as the fleet orchestrator for the world's most advanced chips, ensuring Baseten never experiences a capacity outage while maintaining elite unit economics. To be clear, this is a high-stakes engineering role. You will be hands-on with Kubernetes orchestration while also leading specialized pods focused on the next generation of hardware, like NVIDIA’s Blackwell (B200) architecture. EXAMPLE INITIATIVES The B200 Frontier: Architecting the infrastructure readiness and deployment strategy for Baseten's first Blackwell GPU clusters. Global Workload Orchestration: Building "Multi-cloud Capacity Management" systems to move customer workloads seamlessly across regions to optimize cost and latency. Precision GPU Triage: Developing automated Go-based operators to identify, cordon, and repair unhealthy H100 nodes in under an hour. The Supply Chain of Intelligence: Partnering with l
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