Cloud Platform Engineer Salary Guide Jobs

About the team The Applied AI Engineering (AAE) team is responsible for helping developers and enterprises turn the potential of generative AI into real-world impact. We act as trusted advisors and technical partners to customers and ecosystem partners, helping identify high-impact AI use cases and bring them into production through strong architectural guidance and hands-on execution. The Partner Applied AI Engineering organization works closely with strategic cloud providers, systems integrators, consultancies, and implementation partners to scale successful adoption of OpenAI technologies. As the leader of the AWS Partner AAE pod, you will manage a team of Applied AI Engineers focused on enabling AWS-aligned partners and their customers to build, deploy, and operationalize AI applications on OpenAI’s platform. About the role We are seeking a Manager, Partner Applied AI Engineering – AWS to lead a team of Applied AI Engineers supporting strategic AWS ecosystem partnerships. In this role, you will own the technical success strategy for AWS-aligned partners and help build scalable, repeatable ways for partners and their customers to adopt OpenAI technologies. Your team will guide partners and customers across the full AI implementation lifecycle—from identifying and shaping high-value use cases to solution design, architecture, production deployment, optimization, and adoption growth. You will work cross-functionally with internal and external stakeholders across Sales, Partnerships, Product, Research, and Engineering to ensure the voice of partners and customers informs our platform roadmap and how we bring OpenAI technology into production at scale. This role requires a blend of technical depth, customer leadership, operational rigor, and people management. Success will be measured through production deployments, partner technical maturity, API adoption growth, team development, and the overall impact of the AWS partner ecosystem. This role is based in our San Fra

About the team OpenAI’s mission is to build safe artificial general intelligence (AGI) that benefits all of humanity. Achieving this requires bringing together world-class scientists, engineers, and business leaders to translate frontier research into real-world impact. Within OpenAI, the Go-to-Market organization helps customers understand, adopt, and scale our products across their businesses. The team includes Sales, Solutions, Support, Marketing, Partnerships, and Strategic Pursuits professionals who work together to bring the benefits of AI to organizations globally. About the role We are hiring a Senior Specialist Seller to join the Strategic Pursuits team and lead priority opportunities generated through the joint AWS and OpenAI co-sell motion. You will partner closely with Account Directors, AWS field teams, and cross-functional stakeholders to identify, shape, advance, and close high-value strategic enterprise engagements. This role is ideal for a senior seller with deep experience in enterprise technology, AI, cloud, or complex transformation sales motions. You should be comfortable operating in executive-facing environments, aligning multiple stakeholders, and turning customer priorities into commercially compelling and technically credible opportunities. This role is based in San Francisco, Seattle, or New York. We operate on a hybrid model of 3 days per week in office and offer relocation support. We are also open to remote candidates based in the United States. In this role, you will: Lead commercial execution of priority AWS/OpenAI co-sell opportunities across strategic enterprise accounts. Identify and qualify high-potential opportunities focused on GenAI adoption, frontier platform use cases, and enterprise-wide transformation. Partner with AWS and OpenAI field teams to align account strategy, messaging, stakeholder mapping, and execution plans. Develop customer-facing value propositions that connect OpenAI capabilities with business priorities and

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. Specifically, you'll be working on Modal's machines layer: the fleet of bare metal and cloud hosts that every Function, Sandbox, and training job runs on, and the control plane that provisions, images, monitors, and repairs them. You'll automate the integration of new capacity from a growing set of hardware providers; from auditing and benchmarking hosts and clusters, to maintaining our machine images, configuring GPUs, RDMA, networking, and storage, and getting machines into production. You'll build the automation that keeps the fleet healthy without human intervention: detecting bad GPUs, thermals, and disks. You'll dig into whatever is between the hardware and the software that runs on

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. Specifically, you'll be working on the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You'll make cold starts feel local when the data is hundreds of milliseconds away, designing the caching, preloading, and peer-to-peer layers that hide object-store latency and keep public ingress off saturated uplinks. You'll own durability and cost at petabyte scale, from streaming and batch replication between origins, to garbage collecti

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 a strong technical lead to guide the engineers designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. You'll lead the team responsible for Modal's machines layer: the fleet of bare metal and cloud hosts that every Function, Sandbox, and training job runs on, and the control plane that provisions, images, monitors, and repairs them. You'll own the full lifecycle of a machine, from accepting and benchmarking new hardware from a growing set of providers, to network bring-up, kernel and image management, GPU and disk health tracking, and automated remediation of unhealthy hosts. You'll manage a team of 3–8 engineers while staying hands-on across the stack which involves BMCs, firmware, PXE, bootloaders, Linux networking, drivers, and distributed control-plane services, and you'll shape our long-

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 a strong technical lead to guide the engineers designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. You'll lead the team responsible for the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You'll set technical direction for the primitives that other teams (filesystems, training, sandboxes) build on, balancing durability, latency, throughput, and cost. You'll own the roadmap from today's hardest problems (garbage collection at petabyte scale, active-active replication, rate limiting that protects the upstream without wasting ut

Own the architecture of Myntra’s new product platforms to drive business results Drive and own the architecture and design of some of the most advanced & complex software systems / products in the industry to create company wide impact Help build, mentor and coach a team of very talented Engineers, Architects, Quality engineers, System Operation Engineers and DevOps engineers in architectural and design best practices Experience in distributed systems, cloud service development, deployment and delivery Accountable for the design, for the ease of evolution, quality of the systems, performance, scaling, and availability characteristics and limitations of the systems Envision and develop the long-term architectural direction, with emphasis on platforms/ reusable components while adopting an agile delivery process. Establish structures and processes that ensure a high level of quality and reliability and extensibility of deliverables Drive the creation of next generation extensible web, mobile and fashion commerce platforms, security protocols, customisation and tools to support continuous scaling, internationalisation and platform extensions Drive code and design reviews of components / systems / products in scope and drives the architectural governance for them Set directional paths for the teams/department for adoption of new technology stacks for solving business problems Represent multiple technology domains and Myntra in external technical forums Work with product management, business stakeholders and other engineering leaders to help define mid-term, long-term roadmaps and shape business directions Initiate and deliver leadership training within the engineering organisation, including training new managers, and drive the growth of leaders to create a strong leadership bench. Qualifications & Experience 8+ years of experience in software product development Must have a degree in Computer Science o

Roles and Responsibilities Own the architecture of Myntra’s new product platforms to drive business results Drive and own the architecture and design of some of the most advanced & complex software systems / products in the industry to create company wide impact Help build, mentor and coach a team of very talented Engineers, Architects, Quality engineers, System Operation Engineers and DevOps engineers in architectural and design best practices Experience in distributed systems, cloud service development, deployment and delivery Accountable for the design, for the ease of evolution, quality of the systems, performance, scaling, and availability characteristics and limitations of the systems Envision and develop the long-term architectural direction, with emphasis on platforms/ reusable components while adopting an agile delivery process. Establish structures and processes that ensure a high level of quality and reliability and extensibility of deliverables Drive the creation of next generation extensible web, mobile and fashion commerce platforms, security protocols, customisation and tools to support continuous scaling, internationalisation and platform extensions Drive code and design reviews of components / systems / products in scope and drives the architectural governance for them Set directional paths for the teams/department for adoption of new technology stacks for solving business problems Represent multiple technology domains and Myntra in external technical forums Work with product management, business stakeholders and other engineering leaders to help define mid-term, long-term roadmaps and shape business directions Initiate and deliver leadership training within the engineering organisation, including training new managers, and drive the growth of leaders to create a strong leadership bench. Qualifications & Experience 8+ years of experience in software product development Must have a d

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Forward Deployed AI Engineering Manager on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineeri

Senior React Native Mobile and Full Stack Developer Description - We are seeking a highly skilled Senior React Native Mobile and Full Stack Developer to design, develop, and maintain secure, scalable, enterprise-grade mobile applications for iOS and Android , as well as the cloud services and APIs that support them. The ideal candidate brings extensive experience building production-ready cross-platform mobile applications with React Native , combined with strong backend and cloud development expertise using object-oriented programming languages such as C#, Java, Python, or Go to deliver secure, end-to-end solutions. This role requires deep expertise in mobile authentication , secure storage , offline-first architecture , data synchronization , push notifications , GPS/location services , and mobile security best practices , as well as experience designing and developing RESTful APIs , integrating with cloud platforms such as Microsoft Azure, or AWS , and building scalable backend services. You will work closely with Product Managers, UX Designers, Security Architects, Backend Engineers, and QA teams to deliver high-quality, mission-critical mobile solutions used by enterprise customers worldwide. The ideal candidate is a hands-on specialist who is passionate about building high-quality software, driving architectural decisions, mentoring engineers, and delivering reliable, secure, and performant mobile experiences across the full technology stack. Key Responsibilities Design, develop, and maintain secure, scalable, and high-performance cross-platform mobile applications using React Native for both iOS and Android . Design, develop, and maintain backend APIs , cloud services, and supporting infrastructure that

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 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 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 Stockholm 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 The Role & Team Amplitude is only as useful as the data inside it. The Data Connections team owns how that data gets in and out — importing behavioral and customer data from cloud data warehouses like Snowflake, Databricks, and BigQuery, from cloud object storage like S3 and Azure Blob Storage, and pushing enriched event data back out to warehouses, object storage, streaming destinations, and downstream advertising and marketing platforms. That means batch and streaming pipelines moving billions of events a day, connections that have to keep working across dozens of customer-controlled systems, credentials and configuration that have to stay correct and secure, and latency and reliability targets that customers build their own pipelines on top of. Recent work includes launching new warehouse export destinations, migrating our import pipelines onto a durable workflow engine, building low-latency streaming export, and supporting cross-region and cross-cloud customer storage. You'll lead a team of around 10 engineers building this, reporting to our Head of Data Platform, and you'll be the person accountable for the roadmap, the reliability, and the growth of the people on it. The stack is Java, Temporal, Kafka, Kubernetes, Terraform, DynamoDB, S3, and Snowflake, running on AWS and GCP. Responsibilities Set the direction and roadmap for data import and export, with clear priorities and tradeoffs you can explain to engineers, PMs, and customers Lead, coach, and grow a team of around 10 engineers — hiring, career development, feedback, and performance Partner with your tech leads on architecture across ingestion, transformation, and delivery, without becoming the bottleneck for every decision Own reliability, SLOs, and cost efficiency for pipelines customers depend on daily Expand the set of destinations and sources we support, and make each new integration cheaper to build than the last Work directly with Product, Design, and other Data Platform teams to ship e

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 We are seeking a highly technical and experienced Engineering Manager to one of our business critical engineering team. This role is ideal for a hands-on leader who thrives in a fast-paced environment, has a deep understanding of collaborative document editing technologies, and is passionate about building scalable, high-performance software. As the Manager, you will oversee the development and delivery of innovative features, ensure technical excellence, and mentor a team of talented engineers. The Role: Technical Leadership : Provide hands-on technical guidance to the team, ensuring best practices in software development, architecture, and design. Team Management : Lead, mentor, and grow a team of engineers, fostering a culture of collaboration, innovation, and continuous improvement. Product Development : Drive the development of new features and enhancements, ensuring high performance, scalability, and reliability. Collaboration : Work closely with product managers, designers, and other engineering teams to align on goals, prioritize initiatives, and deliver exceptional user experiences. Code Quality : Oversee code reviews, ensure adherence to coding standards, and advocate for clean, maintainable, and testable code. Innovation : Stay up-to-date with the latest trends and technologies in collaborative editing, cloud infrastructure, and web development, and apply them to improve our product. Operational Excellence : Ensure the stability and performance of the Docs platform, proactively addressing technical debt and optimizing system architecture. Qualifications: Technical Expertise : Proficiency in