Cloud Platform Engineering Jobs

About the team and role The team focuses on SaaS application protection (e.g., Microsoft Office 365, Salesforce). As the industry moves toward SaaS, data protection (backup and recovery) for these applications is critical. You’ll tackle problems at a massive scale, such as efficiently protecting data for millions of users’ emails and documents, helping drive the next generation of SaaS protection and Rubrik’s next growth engine. Key responsibilities (time allocation) Build large-scale, fault-tolerant distributed software systems that can scale indefinitely (35% of time) Own, design, and develop cutting-edge solutions for Disaster Recovery as a Service (DRaaS) for on‑prem and major cloud platforms; Implement data management jobs for backup and recovery of virtual machines in virtualized enterprise infrastructure (Scala/Java); Design and implement admin-facing UIs and intuitive APIs that integrate with third-party and customer applications Perform code reviews focused on interface design, code quality, and testing strategies Solve challenging scalability and stability problems impacting delivery of high‑scale products in accordance with quality, velocity, and coding standards (25% of time) Analyze defects to assess and prioritize fixes; work with customers and product to understand requirements and requested customizations before implementation Respond to critical problems in our Saas product offerings (20% of time) resolve issues in build and test infrastructure; create solutions with robust monitoring, metrics, and automation Partner closely with Rubrik product teams to understand customer requirements and ensure features are delivered effectively (20% of time) What you’ll do (summary) Design, build, and maintain Rubrik’s cloud data protection services for SaaS applications Tackle complex distributed systems and scaling problems Collaborate with Product Management, UI, Documentation, and Support teams Lead projects and mentor junior engineers

Senior GenAI Engineer Location: Charlotte, NC | Practice Area: Technology & Engineering | Type: Permanent Build and scale cutting-edge generative AI solutions that drive real business impact The Role As part of Capco’s Technology Delivery Team, you will bring hands-on experience in agile delivery and engineering best practices to develop innovative AI-driven solutions. As a Senior GenAI Engineer, you will contribute across the full AI lifecycle—from experimentation and prototyping through to production deployment—helping deliver scalable, high-impact solutions for financial services clients. What You’ll Do Design and build applications using foundation models and modern GenAI techniques (e.g., RAG, agent-based workflows) Develop and experiment with autonomous or semi-autonomous agent frameworks Contribute to full-stack AI solutions, including backend services, APIs, and user-facing components Deploy and scale AI/ML solutions in cloud environments (AWS, Azure, or GCP) Collaborate with cross-functional teams and support knowledge sharing across the team What We’re Looking For Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related field (or equivalent experience) ~5+ years of software engineering experience with exposure to AI/ML or data-driven applications Hands-on experience with LLMs or generative AI Strong Python skills and experience building scalable backend systems Experience working with cloud platforms and modern development practices Willingness to work in our office 3 days/week Bonus Points For Experience with GenAI concepts such as RAG, embeddings, vector databases, or agent-based systems Familiarity with MLOps/LLMOps tools and model lifecycle management Experience contributing to full-stack development across backend and frontend Interest in staying current with emerging AI trends and technologies Experience mentoring or supporting team development Why Join Capco Deliver high-impact technology solutions for Tier 1 financial

Senior GenAI Engineer Location: Orlando, FL | Practice Area: Technology & Engineering | Type: Permanent Build and scale cutting-edge generative AI solutions that drive real business impact The Role As part of Capco’s Technology Delivery Team, you will bring hands-on experience in agile delivery and engineering best practices to develop innovative AI-driven solutions. As a Senior GenAI Engineer, you will contribute across the full AI lifecycle—from experimentation and prototyping through to production deployment—helping deliver scalable, high-impact solutions for financial services clients. What You’ll Do Design and build applications using foundation models and modern GenAI techniques (e.g., RAG, agent-based workflows) Develop and experiment with autonomous or semi-autonomous agent frameworks Contribute to full-stack AI solutions, including backend services, APIs, and user-facing components Deploy and scale AI/ML solutions in cloud environments (AWS, Azure, or GCP) Collaborate with cross-functional teams and support knowledge sharing across the team What We’re Looking For Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related field (or equivalent experience) ~5+ years of software engineering experience with exposure to AI/ML or data-driven applications Hands-on experience with LLMs or generative AI Strong Python skills and experience building scalable backend systems Experience working with cloud platforms and modern development practices Willingness to work in our office 3 days/week Bonus Points For Experience with GenAI concepts such as RAG, embeddings, vector databases, or agent-based systems Familiarity with MLOps/LLMOps tools and model lifecycle management Experience contributing to full-stack development across backend and frontend Interest in staying current with emerging AI trends and technologies Experience mentoring or supporting team development Why Join Capco Deliver high-impact technology solutions for Tier 1 financial institutions W

Generative AI Architect Location: Charlotte, NC | Practice Area: Technology & Engineering | Type: Permanent Shape the architecture of enterprise-scale generative AI solutions at the forefront of innovation The Role As part of Capco’s Technology Delivery Team, you will apply deep expertise in architecture, AI, and modern engineering practices to design and deliver next-generation solutions. As a Generative AI Architect, you will lead the definition and implementation of scalable, secure, and enterprise-grade AI systems, guiding projects from concept through to production while aligning technology with strategic business goals. What You’ll Do Define and deliver enterprise-wide architecture for generative AI and agentic systems aligned to business objectives Design scalable, modular solution patterns and integrate foundation models into enterprise environments Architect and implement agentic AI systems, including workflows, orchestration, and system integrations Establish robust cloud-native infrastructure and MLOps pipelines for deployment, monitoring, and lifecycle management Collaborate across teams, mentor colleagues, and contribute to innovation and thought leadership in AI What We’re Looking For Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related field 10+ years of experience in software architecture, including hands-on work with AI/ML systems Strong expertise in generative AI, foundation models, and agentic AI frameworks Proficiency in Python and experience with leading AI/ML frameworks and cloud platforms (AWS, Azure, or GCP) Proven ability to communicate complex technical concepts and influence technical decision-making WIllingness to work in our office 3 days/week Bonus Points For Experience with prompt engineering and advanced RAG-based architectures Familiarity with vector databases and unstructured data processing techniques Experience implementing MLOps frameworks and production-grade AI systems Exposure to containerized and distrib

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Staff Software Engineer, you will orchestrate the implementation of vertical features and horizontal capabilities to include mentoring other engineers on defining requirements with stakeholders and communication tradeoffs of technical implementations on feature and capabilities until they are accepted by the stakeholders. You will: Orchestrate feature implementation across the Federal engineering team to ensure architectural consistency. Define technical strategy for agentic guardrails, explainability, and fleet orchestration. Ensure system reliability and performance across multiple security classifications and network types. Mentor engineers in the process of defining requirements with stakeholders and gathering acceptance. Communicate high-level technical trade-offs and implementation strategies to senior government stakeholders and Scale C-Suite members. Influence the long-term product strategy and technical roadmap for the Federal business unit. Consult on the architecture of AI-powered solutions for large-scale federal contracts. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in

Principal Backend Engineer – Java Location: London (Hybrid) | Practice Area: Technology & Engineering | Type: Permanent Build scalable backend solutions that help shape the future of financial services. The Role Capco is growing our Engineering team, and we’re looking for experienced Principal Backend Engineers with strong Java skills and a passion for delivering innovative solutions in financial services. As a Principal Backend Engineer at Capco, you’ll contribute to high-impact, client-facing projects and work with cloud-native technologies across different domains within Financial Services & Energy. You’ll collaborate with talented engineers, contribute to architecture and engineering decisions, and have access to industry-leading learning and development opportunities. You’ll also use approved AI tools, automation and AI-enabled engineering workflows where appropriate to improve development speed, quality and productivity, while applying human judgement, responsible AI guardrails and appropriate review. What You’ll Do Build and deliver scalable backend services using Java 11, 17+, designing APIs and microservices for enterprise systems. Work across cloud platforms, particularly AWS, applying cloud-native deployment techniques and contributing to architecture and solution design. Develop robust automated test coverage across unit, component, integration, end-to-end and performance testing. Collaborate with clients, product managers and engineers in agile teams to design, deliver and troubleshoot large-scale distributed systems. Use approved AI tools, automation and AI-enabled workflows to support engineering activities such as development, testing, troubleshooting and documentation, with appropriate human review and responsible AI controls. What We’re Looking For Expertise in Java 11, 17+ and Spring Boot, with experience designing and delivering large-scale enterprise backend systems. Experience with cloud-native and distributed architectures, including m

Role Overview You’re a seasoned Site Reliability Engineer who loves owning complex infrastructure, making things run faster, safer, and with less manual effort. In this Staff‑level role, you’ll design and operate VMware‑based private cloud platforms that power mission‑critical SaaS products used by customers around the world. You’ll work across Linux, Windows Server, networking, storage, and automation frameworks to increase reliability, reduce toil, and modernize a global datacenter environment. You’ll have the scope to set technical direction, build automation at scale, and mentor engineers while staying hands‑on with VMware vSphere, F5/AVI load balancers, and hybrid Active Directory. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead the architecture, deployment, and ongoing optimization of VMware vSphere–based private cloud infrastructure across multiple global datacenters. Design and build automation using PowerShell/PowerCLI, Ansible, Python, and CI/CD tools to streamline provisioning, configuration, and compliance. Administer, harden, and troubleshoot Linux (RHEL/CentOS/Ubuntu) and Windows Server environments that host enterprise and SaaS workloads. Integrate and manage Active Directory for authentication, access control, and service accounts across hybrid on‑prem and cloud environments. Partner with network and security teams to manage firewalls, VPNs, storage, and load balancers (F5 BIG‑IP, AVI/NSX Advanced Load Balancer) for highly available services. Document architectures and runbooks, participate in on‑call and change management, and mentor engineers while influencing long‑term reliability and automation strategy. These are the essentials you’ll need to get an interview 10+ years of experience in systems or infrastructure engineering, including operating large‑scale enterprise or SaaS datacenter environments. Deep hands‑on expertise with VMware vSphere (ESXi, vCenter, DRS, HA, vMotion, distributed switches) in production

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Our Inference team is responsible for building and scaling the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry’s largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. The team has a dual mandate: maximizing compute efficiency to reliably serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms. Inference systems are highly performance sensitive distributed systems. Inference serves hundreds of thousands of customers every day, and the size & span of the inference fleet requires sophisticated routing, scaling, and networking systems. Key responsibilities Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide Develop resilient, flexible systems that adapt in real time to real world events Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators and multiple cloud providers Maximize compute efficiency and optimize cost across the fleet by autoscaling and orchestrating production, research, and experimental workloads across multiple cloud providers Build and operate production-grade deployment pipelines for releasing new models to user

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry’s largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. The team has a dual mandate: maximizing compute efficiency to reliably serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms. Inference systems are highly performance sensitive distributed systems. Inference serves hundreds of thousands of customers every day, and the size & span of the inference fleet requires sophisticated routing, scaling, and networking systems. Key responsibilities Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide Develop resilient, flexible systems that adapt in real time to real world events Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators Maximize compute efficiency across the fleet by autoscaling and orchestrating production, research, and experimental workloads Build and operate production-grade deployment pipelines for releasing new models to users Provide high-performance inference infrastructure that enables researcher

Generative AI Architect Location: New York, NY & Orlando, FL | Practice Area: Technology & Engineering | Type: Permanent Shape the architecture of enterprise-scale generative AI solutions at the forefront of innovation The Role As part of Capco’s Technology Delivery Team, you will apply deep expertise in architecture, AI, and modern engineering practices to design and deliver next-generation solutions. As a Generative AI Architect, you will lead the definition and implementation of scalable, secure, and enterprise-grade AI systems, guiding projects from concept through to production while aligning technology with strategic business goals. What You’ll Do Define and deliver enterprise-wide architecture for generative AI and agentic systems aligned to business objectives Design scalable, modular solution patterns and integrate foundation models into enterprise environments Architect and implement agentic AI systems, including workflows, orchestration, and system integrations Establish robust cloud-native infrastructure and MLOps pipelines for deployment, monitoring, and lifecycle management Collaborate across teams, mentor colleagues, and contribute to innovation and thought leadership in AI What We’re Looking For Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related field 10+ years of experience in software architecture, including hands-on work with AI/ML systems Strong expertise in generative AI, foundation models, and agentic AI frameworks Proficiency in Python and experience with leading AI/ML frameworks and cloud platforms (AWS, Azure, or GCP) Proven ability to communicate complex technical concepts and influence technical decision-making WIllingness to work in our office 3 days/week Bonus Points For Experience with prompt engineering and advanced RAG-based architectures Familiarity with vector databases and unstructured data processing techniques Experience implementing MLOps frameworks and production-grade AI systems Exposure to c

Generative AI Architect Location: New York, NY & Orlando, FL | Practice Area: Technology & Engineering | Type: Permanent Shape the architecture of enterprise-scale generative AI solutions at the forefront of innovation The Role As part of Capco’s Technology Delivery Team, you will apply deep expertise in architecture, AI, and modern engineering practices to design and deliver next-generation solutions. As a Generative AI Architect, you will lead the definition and implementation of scalable, secure, and enterprise-grade AI systems, guiding projects from concept through to production while aligning technology with strategic business goals. What You’ll Do Define and deliver enterprise-wide architecture for generative AI and agentic systems aligned to business objectives Design scalable, modular solution patterns and integrate foundation models into enterprise environments Architect and implement agentic AI systems, including workflows, orchestration, and system integrations Establish robust cloud-native infrastructure and MLOps pipelines for deployment, monitoring, and lifecycle management Collaborate across teams, mentor colleagues, and contribute to innovation and thought leadership in AI What We’re Looking For Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related field 10+ years of experience in software architecture, including hands-on work with AI/ML systems Strong expertise in generative AI, foundation models, and agentic AI frameworks Proficiency in Python and experience with leading AI/ML frameworks and cloud platforms (AWS, Azure, or GCP) Proven ability to communicate complex technical concepts and influence technical decision-making WIllingness to work in our office 3 days/week Bonus Points For Experience with prompt engineering and advanced RAG-based architectures Familiarity with vector databases and unstructured data processing techniques Experience implementing MLOps frameworks and production-grade AI systems Exposure to c

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry’s largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. The team has a dual mandate: maximizing compute efficiency to reliably serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms. Inference systems are highly performance sensitive distributed systems. Inference serves hundreds of thousands of customers every day, and the size & span of the inference fleet requires sophisticated routing, scaling, and networking systems. Key responsibilities Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide Develop resilient, flexible systems that adapt in real time to real world events Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators Maximize compute efficiency across the fleet by autoscaling and orchestrating production, research, and experimental workloads Build and operate production-grade deployment pipelines for releasing new models to users Provide high-performance inference infrastructure that enables researcher

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry’s largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. The team has a dual mandate: maximizing compute efficiency to reliably serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms. Inference systems are highly performance sensitive distributed systems. Inference serves hundreds of thousands of customers every day, and the size & span of the inference fleet requires sophisticated routing, scaling, and networking systems. Key responsibilities Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide Develop resilient, flexible systems that adapt in real time to real world events Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators Maximize compute efficiency across the fleet by autoscaling and orchestrating production, research, and experimental workloads Build and operate production-grade deployment pipelines for releasing new models to users Provide high-performance inference infrastructure that enables researcher

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry's largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. The team has a dual mandate: maximizing compute efficiency to serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms. As a Staff Software Engineer on our Inference team , you will work end to end, identifying and addressing key infrastructure blockers to serve Claude to millions of users while enabling breakthrough AI research. Strong candidates should have familiarity with performance optimization, distributed systems, large-scale service orchestration, and intelligent request routing. Familiarity with LLM inference optimization, batching strategies, and multi-accelerator deployments is highly encouraged but not strictly necessary. Strong candidates may also have experience with: High-performance, large-scale distributed systems Implementing and deploying machine learning systems at scale Load balancing, request routing, or traffic management systems LLM inference optimization, batching, and caching strategies Kubernetes and cloud infrastructure (AWS, GCP) Pytho

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry's largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. Inference systems are highly performance sensitive distributed systems. Inference serves hundreds of thousands of customers every day, and the size & span of the inference fleet requires sophisticated routing, scaling, and networking systems. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms. Key responsibilities Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide Develop resilient, flexible systems that adapt in real time to real-world events Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators Maximize compute efficiency across the fleet by autoscaling and orchestrating production, research, and experimental workloads Build and operate production-grade deployment pipelines for releasing new models to users Provide high-performance inference infrastructure that enables researchers to develop next-generation models Integrate new AI accelerator platforms and support inference for new model architectures Minimum qualifications Proficiency in Python or Rust Software engineering experience building and operating distributed systems in produ