Cloud Devops Engineer Salary India in United States

NVIDIA's GeForce Now, the next-generation gaming service powered by NVIDIA GPUs in the cloud, transforms a Mac, any PC, or just a mobile device into a high-performance gaming rig. GeForce NOW automatically keeps games up-to-date, and users around the globe can instantly stream the latest games in high-definition resolution at the lowest latency for the smoothest gameplay. Just click and play! Visit us at https://www.nvidia.com/en-us/geforce-now. In addition to gaming, the state-of-the-art low-latency streaming technology has expanded to a new range of applications, including augmented and virtual reality, artificial intelligence, and robotics. We are now looking for a Senior Software Engineer – Streaming with strong C++ skills and a deep interest in streaming technologies to join a team of highly skilled and motivated software engineers who help build the next generation of applications with media and data streaming capabilities. Now, are you passionate about driving this technology to its edge? Do you understand various streaming protocols? Can you solve complicated problems and propose innovative solutions? Then, we are keen to hear from you. What you’ll be doing: Design, develop, optimize, and debug C++ software for ultra low-latency streaming systems. Build and improve media streaming pipelines using technologies such as WebRTC, GStreamer, RTP/RTCP, and related protocols. Analyze CPU, memory, networking, media pipeline, and scheduling behavior across real-world workloads. Work across Windows, Linux, QNX, applications frameworks, and embedded platforms. Define and implement KPIs for networking quality, streaming quality, and user experience. Integrate streaming softwa

NVIDIA is seeking a Senior Technical Program Manager to join the CSP Engagements team, focused on deep technical engagement with hyperscale cloud service providers for NVIDIA’s next‑generation datacenter systems such as Vera Rubin NVL72. This role is intended for experienced systems and embedded software leaders—including software engineering managers, technical leads, or senior architects—who have led datacenter server and platform software programs and can operate as a trusted technical partner to hyperscale CSP engineering teams. As a member of the CSP Engagements team, you will act as the primary technical engagement leader between NVIDIA’s system software organizations and CSP platform, system software, and AI teams, ensuring alignment, readiness, and successful large‑scale deployment of NVIDIA‑based datacenter solutions. What you will be doing: Lead deep technical engagements with hyperscale CSPs as the primary NVIDIA point of contact for system software, firmware, and platform readiness for NVIDIA datacenter products. Partner directly with CSP system software, firmware, and infrastructure engineering leaders to align on software architecture, bring‑up plans, deployment readiness, and production requirements for NVIDIA‑based server and rack‑scale platforms. Represent CSP technical priorities internally, advocating for customer requirements and tradeoffs across NVIDIA’s system software, firmware, hardware, silicon, and product teams are aligned to customer needs, timelines, and constraints. Own the end‑to‑end CSP engagement lifecycle, from early technical alignment and pre‑production readiness through large‑scale deployment, escalation management, and sustained production support. Drive bi‑directional technical communication: translating CSP system‑level requirements into actionable focus areas for NVIDIA engineering teams, while clearly communicating N

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Staff Software Engineer is responsible for the techno-functional impact analysis, design & code construction activities associated with development of software releases for the CVS Retail Pharmacy systems. Strong technical, functional, and interpersonal skills are key to perform this role successfully. The current suite of systems includes multiple applications including, but not limited, to the Tier 1 systems for Retail Pharmacy. The Staff Software Development Engineer will be involved throughout the entire development life cycle of a product and must be able to deliver an efficient solution, as well as identify and properly mitigate any risks to the product before deployment to production. ** This role is located in RI , Woonsocket** Required qualifications: 7+ years of software development experience in enterprise/web applications 5+ years of experience as full stack developer in Java-based technologies including microservices and spring boot framework /REST 5+ years of experience Cloud Technologies like Azure, GCP or other public cloud services and Knowledge of open-source packages especially those provided by Apache, Google, and Spring 2 + years of experienc

NVIDIA is seeking a Senior Firmware Engineer to join our CSP Engagements team, focusing on system software for Datacenter products such as GB200. This role combines deep technical expertise in embedded firmware development with customer-facing responsibilities to enable cloud service providers with next-generation computing platforms. You will work at the intersection of hardware and software, driving technical solutions from concept through deployment. What you will be doing: Design and develop firmware solutions for manageability and observability of data center servers. Actively participate in hardware bring-up activities, OOB firmware development, protocol stacks (Redfish, PLDM, MCTP, NSM) and hardware-software co-design for Cloud Service Provider deployments. Debug and troubleshoot NVIDIA GPU firmware issues, power management, performance, and thermal control problems for data center deployments, providing active support to CSPs. Partner directly with CSPs to deliver technical solutions, co-develop & co-debug features and optimizations, and provide support during new product introductions. Perform advanced system debugging, root cause analysis, and performance optimization for large-scale data center environments. Collaborate with AE, FAE, and Solution Architect teams to deliver integrated customer solutions and technical documentation. What we need to see: Deep expertise in data center server architectures, HPC systems, and hardware-software co-design. Deep expertise in embedded firmware, server management controllers, and hardware bring-up with proven track record of shipping production BMC solutions Strong knowledge of DMTF protocols (Redfish, IPMI, PLDM, MCTP, SPDM), telemetry frameworks, and out-of-band management architectures Expert-level skills in C/C&

About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. Working alongside leading cloud providers, engineering firms, construction partners, utilities, and equipment manufacturers, we are delivering hyperscale AI campuses that enable the next generation of frontier AI models. The Strategic Sourcing team develops and executes the commercial strategies that ensure our infrastructure programs have reliable access to the equipment, materials, and strategic partners needed to deliver at unprecedented scale. We partner closely with Infrastructure Delivery, Capacity Planning, Design Engineering, Hardware Operations, Finance, Legal, and our external suppliers to build a resilient global supply network capable of supporting Industrial Compute's long-term growth. As we continue expanding globally, strategic sourcing becomes a critical competitive advantage, ensuring our infrastructure programs remain cost-effective, resilient, and capable of executing against aggressive deployment timelines. About the Role We are seeking a Strategic Sourcing Manager, Data Center Infrastructure: Owner Furnished Equipment to lead sourcing strategy for the critical infrastructure systems that power Industrial Compute campuses. This role will develop commercial strategies, negotiate strategic supplier agreements, and manage relationships across engineering, construction, manufacturing, and infrastructure partners responsible for delivering mission-critical facilities. You will work closely with Infrastructure Delivery, Capacity Planning, Engineering, Finance, Construction, and external suppliers to ensure Industrial Compute has the capacity, supplier relationships, and commercial frameworks required to support rapid global expansion. The ideal candidate has experience sourcing major infrastructure systems for hyperscale data centers, mission-critical facilities, industrial construction, semiconductor manufacturing, energy infrastr

Our Strategic Account Executives target and close new business with Datadog’s largest, most strategic customers and prospects. In this role you’ll be focused on uncovering the pain points organizations face as they operate in or migrate to a cloud environment at scale as well as delivering the appropriate Datadog solution. 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: Prospect into large Fortune 1000 companies while running an efficient sales process Maintain, build and own specific relationship maps for your territory including existing relationships and aspirational contacts Develop a deep comprehension of customer's business Negotiate favorable pricing and business terms with large commercial enterprises by selling value and ROI Handle existing customer expectations while expanding reach and depth into assigned territory Demonstrate resourcefulness when faced with challenges that defy easy solution Have intuitive sense of necessary steps to close business and gain customer validation Identify robust set of business drivers behind all opportunities Ensure high forecasting accuracy and consistency Who You Are: Someone with 5+ years closing experience (mix of field selling within mid-market and enterprise) Driven and have met/exceeded direct sales goals of 1M+ and operated with an average deal size of $100k+ Able to demonstrate methodology to prospect and build pipeline on your own Experienced in working for an innovative tech company (SaaS, IT infrastructure or similar preferred) Experienced in selling into large Fortune 1000 companies with the ability to win new logos Role requires regular travel to client sites, within your area and other regions, using various modes of transportation (car, train, air), depending on business needs Datadog valu

About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. In partnership with leading cloud providers, hardware manufacturers, utilities, construction partners, and internal engineering organizations, we are delivering hyperscale AI campuses that power the next generation of frontier AI models. Infrastructure Delivery Operations sits at the center of this effort. Our team develops the operating model that connects infrastructure strategy, supply planning, manufacturing operations, and delivery into a single, integrated system that enables OpenAI to deploy AI infrastructure predictably at scale. We partner across Hardware Engineering, Network Engineering, Capacity Delivery, Hardware Operations, Security, Finance, Strategic Sourcing, and external infrastructure partners to create a single, integrated view of program health. Through governance, operational analytics, executive reporting, and scalable operating mechanisms, we enable leaders to proactively manage risk, optimize capacity, and deliver infrastructure predictably at Industrial Compute speed. About the Role We are seeking a Technical Program Manager, Infrastructure Delivery Operations to drive integrated strategy and delivery across OpenAI's rapidly expanding AI infrastructure portfolio. This role sits at the intersection of infrastructure strategy, New Product Introduction (NPI), supply planning, manufacturing operations, and infrastructure delivery. You will lead highly cross-functional programs spanning engineering, supply planning, manufacturing, logistics, construction, commissioning, and operations, ensuring technical and operational dependencies remain synchronized from planning through production readiness. Beyond driving program execution, you will leverage operational insights to improve capacity planning, infrastructure strategy, and deployment readiness. You will also help operationalize new technologies and suppliers by partnering w

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: We’re looking for business operations managers to join the team. This person will work closely with folks across marketing, sales, operations, and finance across a variety of initiatives to help scale the business in our next phase of growth. You'll be a generalist who gets in the weeds on all the business and operational aspects of a high-growth startup. In this role, you will: Drive in-depth quantitative analyses to inform our pricing and packaging strategy. Help spin up our deal desk and streamline enterprise deals. Support the exec team on various finance functions, from investor relations to large cloud vendor negotiations to identifying cost optimization opportunities. Implement new tools and processes to enable the GTM org to grow rapidly. Get creative on a spectrum of ad-hoc projects like securing new office space in Manhattan. Requirements: We are looking

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: We're hiring a Compute Strategy and Operations lead to own how Modal plans for and acquires GPU and CPU capacity. You'll size our infrastructure needs ahead of demand, source supply across hyperscalers, neoclouds, and datacenter operators, and negotiate and close the contracts to secure it. The compute you secure directly determines what Modal can sell and build. In this role, you will: Own end-to-end procurement of GPU and CPU capacity across hyperscalers, neoclouds, and datacenter operators Build and maintain a strong pipeline of supplier relationships Evaluate supply options on price, availability, hardware specs, networking capabilities, and SLA terms Negotiate and close contracts: reserved capacity agreements, spot arrangements, MSAs, DPAs, and order forms Work closely with our engineering teams to translate technical requirements into procurement specs Track

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: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Requirements: 5+ years of experience writing high-quality production code Experience building high-performance distributed systems at a large scale (the more battle scars, the better) Strong cloud skills Strong knowledge of low-level operating system foundations (Linux kernel, file systems, containers, etc.) Experience with performance engineering (tell us a story of when you shaved off a few milliseconds!) Ability to work in-person in our NYC or SF office. Prior experience with Rust is nice to have, but not required. Ability to participate in on-call rotation and respond to production incidents.

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: At Modal, we sell cloud services atop which our customers run their critical production systems. As a rapidly growing new cloud infrastructure company, we seek to improve our reliability dramatically while scaling the size of our platform, customer base, and our team. This role is for people who are deep systems thinkers, love stacking nines, and thrive from making others move faster at scale. Responsibilities include: Identifying architectural changes to improve reliability and performance. Fostering a culture of reliability across Modal’s engineering organization. Defining and implementing operational processes such as deployments, upgrades, etc. Operating systems like Kubernetes, Postgres, Redis, etc. Participating in on-call rotations, and responding to production incidents. Requirements: 5+ years of experience writing high-quality production code. 2+ years of

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 We're looking for an Engineering Manager to lead a team of highly experienced engineers building the infrastructure that powers Modal's serverless GPU platform. This is a hands-on leadership role — expect to split your time between technical contribution and people management depending on what the team needs. You'll set direction, remove blockers, and build a strong engineering culture as your team tackles hard problems in distributed computing, large-scale data handling, and performance optimization. Who You Are You're an experienced engineering leader who stays close to the work and builds alongside your team when it counts. You earn trust through technical depth, not title. You communicate clearly, help strong engineers move fast without cutting corners, and stay calm and pragmatic under pressure. You care as much about how your team gets to an answer as the answ

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: We are looking for strong engineers with experience in making ML systems performant at scale. If you are interested in contributing to open-source projects and Modal’s container runtime to push language and diffusion models towards higher throughput and lower latency, we’d love to hear from you! Requirements: 5+ years of experience writing high-quality, high-performance code. Experience working with torch, high-level ML frameworks, and inference engines (vLLM or TensorRT). Familiarity with Nvidia GPU architecture and CUDA. Experience with ML performance engineering (tell us a story about boosting GPU performance — debugging SM occupancy issues, rewriting an algorithm to be compute-bound, eliminating host overhead, etc). Nice-to-have: familiarity with low-level operating system foundations (Linux kernel, file systems, containers, etc).

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: We're looking for Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you'll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads — LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You're helping teams reach outcomes most engineers can't on their own. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads

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: We're looking for strong backend engineers who love building a developer tools used by the largest AI companies in the world. You’ll be building for things at scale, but also for new AI workflows that change every day. Requirements: Experience building and shipping modern web applications end-to-end. We care more about what you’ve built than how many years you’ve been building. Comfort working across the stack: TypeScript on the frontend, Python services on the backend, and ClickHouse for data and analytics. Deep knowledge of observability tools and patterns used for large-scale workloads such as custom sandboxes, training and inference for large language (LLM) and diffusion models. Experience with at least one of: billing/payments systems, B2B SaaS tooling, or enterprise software, or LLM / diffusion models inference and training loads. Strong product instincts; yo