Infrastructure Jobs

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. Join NVIDIA's GPU Performance Infrastructure team and be part of a brand-new journey in validating and shipping next-generation GPU architectures. At NVIDIA, we empower our engineers to innovate and drive powerful performance through innovative infrastructure and workflows. This role is uniquely positioned to influence the entire lifecycle of GPU performance verification, from early-stage modelling to post-silicon validation. With our bold standards and extraordinary team, you'll have the chance to define a significant impact on the future of computing! What you'll be doing: Build and develop end-to-end performance verification infrastructure. Build scalable data pipelines to surface performance metrics from simulation, emulation, and silicon environments. Coordinate with GPU architects to craft infrastructure for performance verification of upcoming architectures. Work closely with HW teams to automate and accelerate verification workflows, enabling faster GPU build iteration. Empower GPU architects by providing insights to understand current performance and model industry-leading performance for future builds. Improve the daily workflows of the wo

Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 200+ public data centers globally and thousands of private sites at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform. We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler. Role We are looking for a Senior Staff Software Engineer – Test Automation Infrastructure (ZIA Core) to join our team. This is a hybrid (3 days per week in San Jose, CA office) role, reporting to the Sr Manager, Software Engineering, QA in the ZIA Engineering team. In this role you will own the architecture, development, and maintenance of a high-scale system test automation infrastructure for ZIA Core Datapath, a cloud security platform processing 400B+ transactions daily. You will build repeatable automation suites for L4-L7 technologies, validate cloud firewall and tunneling stacks, diagnose customer issues, and mentor engineers while driving continuous regression optimization. What you’ll do (Role Expectations) Collaborate with cross-functional teams during design, development, and maintenance of cloud-based software solutions Architect, design, develop, and maintain a scalable system test automation infrastructure for

Location Details: Canada - BC or ON (remote) 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 remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings. Join our team GoDaddy - Global Production Engineering looks after GoDaddy's global infrastructure, in the cloud and on-premises. We are hiring an experienced Technical Program Manager, focused on our AWS cloud infrastructure, to plan, lead and deliver complex cross-team initiatives. This is a heavily coordination-focused role: you will own the execution of a portfolio of AWS cloud platform and cost-savings programs, working hands-on with software engineers, engineering managers and SREs to achieve outcomes aligned with the strategy. You will drive dependencies end-to-end, facilitate trade-off decisions, and give collaborators and leadership clear, reliable access to status and risk. You will be an integral part of the Technical Program Management team, partnering closely with engineering leads to ensure GoDaddy delivers on its planned objectives and global strategy. What you'll get to do... Own end-to-end delivery of a portfolio of concurrent cloud platform programs, coordinating across engineering and partner teams to manage scope, schedule and dependencies against the critical path. Drive cost-savings program coordination, including tracking, reporting and surfacing risks to goals and achievements proactively. Run intake and prioritization processes and keep priority pages and status sources current and trustworthy. Serve as the central coordination point across teams, facilitating trade-off and negotiation discussions, driving alignment, and resolving roadblocks with minimal issues. Build reports, scorecards and dashboards to c

DR ASHWANI KUMAR VIJ : Have been retained by a Growing, Reputed and professionally managed Real Estate Group ( For Their Affordable Housing Project ) to select 1 : General Manager / AGM / Head - Sales - Gurgaon ( Real Estate only). Job Location: Gurgaon Job Description: Hiring and training sales staff Ensuring that department meets its sales targets Plan and assign daily workload to sales team Developing a departmental strategic plan Ensuring customer's expectations are fulfilled Respond to escalated customer complaints in a timely manner Overseeing the budget Represent company brand in sales conference and trade shows Evaluate current sales processes and recommend improvements Identify selling strategies and opportunities to increase revenue Desired Candidate Profile : Candidates must be from Real Estate background, with a minimum experience of 4-5 years in selling affordable housing in gurgaon region. Experienced Professionals having less than 10 years of experience From Real Estate Sector would be considered for the Position of AGM / Head / Senior Manager / Manager - Sales Age Desired : 32-35 Years. MBA / PGDM in Marketing having 10-12 years of relevant experience Preferred. DR ASHWANI KUMAR VIJ : President : Sales Recruitment Email Complete/Structured CV, with Scanned copy of Visiting Card, Salary Drawn / Expected details at:

Mission Systems (MS) Software Test and Infrastructure Manager — USA - Berkeley, MO. Apply via Workday.

Why Harvey At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. Role Overview As a Staff Software Engineer on the Model Infrastructure team, you'll lead the design and development of the systems that power every AI request at Harvey. You'll partner closely with AI Research, Product Engineering, Infrastructure, and external model providers to build a platform that is highly reliable, scalable, observable, and efficient. What You’ll Do Lead the design and implementation of Harvey's Model Infrastructure platform. Build systems to ensure high availability, low latency, and operational excellence for AI inference. Design and improve Harvey's Unified Model Controller (UMC) and Model Selector platform to automatically detect model degradations and intelligently route traffic based on reliability, latency, quality, compliance, and cost. Develop systems

About Vercel: Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience. Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. About the role: We're hiring a DevRel Engineer to work inside the product teams building Vercel's agentic infrastructure: AI Gateway , Sandbox , and the primitives that come after them. You'll sit with product and engineering, build with these tools before anyone else can, and show the world what they make possible. You will report to the Head of AI Infrastructure and can be located anywhere. If you’re based within a pre-determined commuting distance of one of our offices (SF, NY, London, or Berlin), the role includes in-office anchor days on Monday, Tuesday, and Friday, even if the role is listed as remote. For location-specific details, please connect with our recruiting team. When applying, include a link to something you made that taught developers something, a talk, a repo, a post, a video. Applications without one will not be considered. What you will do: Build agents and applications on AI Gateway and Sandbox before they ship, then turn what you learn into demos, templates, and open source projects developers actually clone and run. Teach developers how to build with agentic infrastructure through writing, talks, videos, and live coding. You set the canonical examples the ecosystem emulates. Shape the products themselves. You sit in the same planning meetings as the PMs and engineers, and your job is to hit the rough edges first and make sure they get fixed before launch. Own the important pieces of launches: example repos, launch demos, docs contributions, and the first wave of answers when developers start asking questions. Bring the outs

Why Harvey At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. Role Overview As the Engineering Manager for Model Infrastructure, you'll lead the team responsible for the platform powering every model request across Harvey. You'll partner closely with AI Research, Product Engineering, Infrastructure, and external AI providers to ensure our platform remains reliable, scalable, and cost-efficient as our business grows. Model Infrastructure is one of Harvey's most strategic engineering organizations. Every product capability—from chat experiences and agents to document workflows and future reasoning systems—depends on this platform. Over the next several years, the team will evolve beyond operating third-party models to building the infrastructure that enables Harvey to train, evaluate, deploy, and operate our own frontier AI models. This role off

About BlockTech BlockTech is a fast-paced algorithmic trading firm. Specializing in crypto options, we facilitate global cryptocurrency derivatives and spot trading, while expanding into new markets. As we continue to grow rapidly, we are looking for a Senior Software Engineer to take technical ownership of the data infrastructure our trading and technology teams are built on. Every decision at BlockTech starts with data: exchange feeds, our own trade and account events, and the history we query to make sense of both. The Foundation team owns the systems that move, aggregate, and store all of it. We run our own Kafka, NATS, PostgreSQL, ClickHouse, and Iceberg, self-hosted and tuned by us. We work primarily in Rust, with Python and SQL alongside. This is a role for an engineer who has already built and operated data infrastructure at scale, and who wants their technical decisions to set direction rather than follow it. What will you do? You will own the pipelines and stores every other team depends on. When a researcher backtests a strategy, when a trader checks a position, when risk queries yesterday, they are all reading data your systems ingested, routed, and kept correct. As a senior engineer, you will also set the technical standards the rest of the team builds against. You will: Own the ingest path. Collect public and private exchange information and internal trading data with minimal latency impact, and land it in our trading systems in real time. Architect the streaming layer. Design and operate our Kafka and NATS messaging systems for the throughput and delivery guarantees our critical flows depend on. Build the storage layer. Develop real-time aggregation and long-term storage across PostgreSQL, ClickHouse, and Iceberg, and make the structural calls that keep queries fast as volumes grow. Run what you build. Own capacity, retention, schema evolution, and failure behavior for infrastructure we host ourselves, with no managed service to hide behind. Make the

About Inorsa At Inorsa , we’re not just building technology — we’re shaping the future of the telecom and structural engineering industries. With our groundbreaking automation tools, we are empowering engineers to transform the way critical telecom infrastructure is built, making it safer, faster, and more efficient than ever before. Headquartered in Austin, Texas, and backed by top-tier venture capital, Inorsa is among the fastest-growing and most successful companies in the engineering tech space. We’re revolutionizing how engineers operate, from analyzing complex documents to producing high-quality construction drawings, while providing actionable insights that are changing the game. As we continue to scale, we’re looking for visionary, forward-thinking individuals who are ready to push the boundaries of technology and drive real change. If you’re passionate about solving complex technical problems and making an impact in an industry ripe for disruption, we want to meet you. About the Role norsa is looking for a Technical Account Manager to drive the implementation, adoption, and utilization of our cutting-edge AI and automation products in the telecom industry . In this role, you will serve as a trusted technical advisor to our customers, leveraging your telecom expertise in customer workflows to design and deploy impactful solutions. This is a high-impact, hybrid role designed for a growth SaaS company operating in the telecom infrastructure ecosystem. You will own post-sale customer outcomes end-to-end—from technical onboarding and adoption to value realization, renewal, and product feedback—while also acting as a customer-embedded product partner. This role is ideal for someone who thrives at the intersection of domain expertise, SaaS technology, and custo

Staff Software Engineer - AI Research Infrastructure P-1215 At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform so our customers can focus on the high-value challenges that are central to their own missions. The Databricks AI Research organization enables companies to develop AI models and agents using their own data, with technologies ranging from post-training open source LLMs to developing advanced multi-agent architectures. Databricks AI does so by producing novel science and putting it into production. Databricks AI is committed to the belief that a company’s AI models and agents are just as valuable as any other core IP, and that high-quality AI should be available to all. Job Description As a Staff Software Engineer, AI Research Infrastructure, you will be developing and running the research stack that powers Databricks AI Research. You will design and build services that schedule, orchestrate, and observe large‑scale training and inference experiment workloads across thousands of GPUs, improve our dev tooling and ensure that researchers can iterate quickly without sacrificing reliability, efficiency, or security. You’ll partner closely with research scientists, ML engineers, and platform teams to turn experimental workloads into robust, repeatable pipelines, and to push the limits of what our infrastructure can support. The Impact you will have As a Staff Software Engineer on the AI Research Infra Team at Databricks, you will: Design and implement infrastructure that supports large‑scale experiments, data processing, and model training (e.g., HPC clusters, GPU fleets, or cloud‑based systems) Enable researchers to go from idea to large‑scale experiment in minutes, not days, by building powerful abstractions for job submission, scheduling, and monitoring. Create tooling that improv

About the Team OpenAI’s Hardware organization is building the infrastructure foundation for frontier AI systems. The Supply Chain organization is responsible for enabling scalable, resilient, and efficient supply chains across custom silicon, systems, networking, memory, storage, and rack-scale infrastructure. The Supply Chain Program Manager (SCPM) drives end-to-end material readiness and supply chain execution across the hardware lifecycle, from early architecture and sourcing strategy through production ramp and sustaining operations. We are looking for experienced supply chain leaders who can operate across technical, commercial, and operational domains to ensure material readiness, supply continuity, and execution excellence for complex AI hardware programs. About the Role As a Supply Chain Program Manager, you will own material readiness and supply chain execution for critical hardware programs spanning custom silicon, systems, memory, storage, networking, and rack infrastructure. You will work cross-functionally with Engineering, Strategic Sourcing, Manufacturing Operations, Finance, Planning, Quality, and external suppliers to develop and execute scalable supply strategies that support aggressive product development and deployment timelines. This role requires deep understanding of hardware supply chains, material planning, NPI execution, supplier management, and operational scaling in constrained and rapidly evolving environments. Responsibilities Material Readiness & Supply Planning - Own end-to-end material readiness across NPI and production phases, including building the necessary framework and processes for enablement. Drive supply planning and execution for long lead-time and constrained commodities including ASICs, HBM, DDR, SSDs, networking, optics, power, thermal, and mechanicals. Build and manage material readiness plans aligned to proto/pre-EVT, EVT, DVT, PVT, and mass production schedules. Monitor supply health, lead times, inventory positio

Staff Software Engineer - AI Research Infrastructure P-1215 At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform so our customers can focus on the high-value challenges that are central to their own missions. The Databricks AI Research organization enables companies to develop AI models and agents using their own data, with technologies ranging from post-training open source LLMs to developing advanced multi-agent architectures. Databricks AI does so by producing novel science and putting it into production. Databricks AI is committed to the belief that a company’s AI models and agents are just as valuable as any other core IP, and that high-quality AI should be available to all. Job Description As a Staff Software Engineer, AI Research Infrastructure, you will be developing and running the research stack that powers Databricks AI Research. You will design and build services that schedule, orchestrate, and observe large‑scale training and inference experiment workloads across thousands of GPUs, improve our dev tooling and ensure that researchers can iterate quickly without sacrificing reliability, efficiency, or security. You’ll partner closely with research scientists, ML engineers, and platform teams to turn experimental workloads into robust, repeatable pipelines, and to push the limits of what our infrastructure can support. The Impact you will have As a Staff Software Engineer on the AI Research Infra Team at Databricks, you will: Design and implement infrastructure that supports large‑scale experiments, data processing, and model training (e.g., HPC clusters, GPU fleets, or cloud‑based systems) Enable researchers to go from idea to large‑scale experiment in minutes, not days, by building powerful abstractions for job submission, scheduling, and monitoring. Create tooling that improv

About the Team The GPT Infrastructure team builds systems that turn advances in model inference and optimization into reliable production capabilities. We enable OpenAI workloads to be qualified and optimized across new accelerator platforms without requiring a one-off port and tuning effort for every hardware target. Our work spans distributed systems, model execution, compilers and runtimes, performance engineering, secure partner integrations, evaluation systems, and developer tooling. We build the infrastructure that makes optimization workflows automated, reproducible, and trustworthy. About the Role We are seeking a software engineer to help build the platform that qualifies and optimizes inference workloads across heterogeneous compute environments. You will develop both OpenAI-hosted services and secure partner-side software for running long-lived optimization workflows. These workflows generate candidate kernels, runtime configurations, and serving-stack changes; compile and execute them on target hardware; verify their correctness; measure their performance; and use the results to guide further optimization. You will work across model architecture, distributed execution, compilers, runtimes, networking, and accelerator systems. A central part of the role is turning research prototypes and one-off hardware bring-up efforts into reliable, reusable infrastructure with clear contracts, reproducible results, strong observability, and well-defined security boundaries. Key Responsibilities Design, build, and operate APIs and control-plane services for long-running workload qualification and optimization campaigns, including scheduling, retries, checkpointing, resource budgets, and observability. Build secure partner-side execution and evaluation software that can compile, run, verify, profile, and benchmark candidate artifacts on accelerator hardware. Integrate model workloads, hardware profiles, compiler toolchains, runtimes, serving engines, and distributed-exe

We are looking for an AI Infra engineer to join our growing team. We work with Kubernetes, Slurm, Python, C++, PyTorch, and primarily on AWS. As an AI Infrastructure Engineer, you will be partnering closely with our Inference and Research teams to build, deploy, and optimize our large-scale AI training and inference clusters. Responsibilities Design, deploy, and maintain scalable Kubernetes clusters for AI model inference and training workloads Manage and optimize Slurm-based HPC environments for distributed training of large language models Develop robust APIs and orchestration systems for both training pipelines and inference services Implement resource scheduling and job management systems across heterogeneous compute environments Benchmark system performance, diagnose bottlenecks, and implement improvements across both training and inference infrastructure Build monitoring, alerting, and observability solutions tailored to ML workloads running on Kubernetes and Slurm Respond swiftly to system outages and collaborate across teams to maintain high uptime for critical training runs and inference services Optimize cluster utilization and implement autoscaling strategies for dynamic workload demands Qualifications Strong expertise in Kubernetes administration, including custom resource definitions, operators, and cluster management Hands-on experience with Slurm workload management, including job scheduling, resource allocation, and cluster optimization Experience with deploying and managing distributed training systems at scale Deep understanding of container orchestration and distributed systems architecture High level familiarity with LLM architecture and training processes (Multi-Head Attention, Multi/Grouped-Query, distributed training strategies) Experience managing GPU clusters and optimizing compute resource utilization Required Skills Expert-level Kubernetes administration and YAML configuration management Proficiency with Slurm job scheduling, resource mana