68 Gcp Architect Jobs

Role Overview Were seeking a highly seasoned Solution Architect with deep expertise in Google Cloud Platform (GCP) and a proven track record in designing data and AI infrastructure tailored to AdTech use cases. You'll be pivotal in building scalable, performant, and privacycompliant systems to support realtime bidding, campaign analytics, customer segmentation, and AIdriven personalization. Key Responsibilities Architect and lead GCPnative solutions for AdTech: realtime bidding (RTB/OpenRTB), campaign analytics, lookalike modeling, and audience segmentation. Design highthroughput data pipelines, eventdriven architectures, and unified audience data lakes leveraging GCP services: BigQuery, Dataflow, Pub/Sub, Cloud Storage, Dataproc, Cloud Composer (Airflow), Dataplex , Vertex AI / AutoML , Cloud Functions , Cloud Run , GKE , Looker , and Apigee Collaborate with ad ops, marketing, and product stakeholders to translate business goals into architecture roadmaps, lead discovery workshops, solution assessments, and architecture reviews in presales and delivery cycles nexusitgroup.comSmartRecruiters. Integrate with thirdparty AdTech/MarTech platforms including DSPs, SSPs, CDPs, DMPs, ad exchanges , identity graphs, and consent/identity resolution systems (e.g. LiveRamp, The Trade Desk, Google Ads Data Hub). Ensure architecture aligns with GDPR, CCPA , IAB TCF and data privacy regulations—support consent management, anonymization, encryption, and access controls. Lead multidisciplinary technical teams (Data Engineering, MLOps, Analytics), enforce best practices in data governance, CI/CD, and MLOps (via Cloud Build , Terraform, Kubeflow/Vertex AI pipelines). Mentor engineers, run architecture reviews, define governance, cost optimization, security strategy and system observability. Conduct handson prototyping and PoCs to validate AI/ML capabilities, rapid experimentation before fullscale implementation Machine Learning Jobs. Tech Stack Expertise & Qualifications 15+ years in technical architecture, consulting, or senior engineering roles (preferably with majority in data & analytics); at least 5+ years handson with GCP architectures Indepth knowledge and handson experience of: GCP data and analytics stack: BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, Dataplex, Cloud Storage AI/ML on GCP: Vertex AI, AI Platform, AutoML , model deployment, inference pipelines Compute frameworks: Cloud Functions , Cloud Run , GKE , Apigee Business intelligence and visualization: Looker Infrastructure as code: Terraform ; CI/CD pipelines: Cloud Build , Git-based workflows Skilled in Python and SQL ; familiarity with Java or Scala is a plus. Experience designing eventdriven architectures, streaming data pipelines, microservices , and APIbased integrations. Proven AdTech domain expertise: programmatic advertising, RTB/OpenRTB, identity resolution, cookieless frameworks, DMPs/CDPs data flows . Proven experience with data governance, encryption, IAM, PII anonymization , privacy-enhancing tech. Strong ability to code prototypes or PoCs to solve client challenges quickly, with high-quality architectural foundations Excellent communication skills, able to clearly present complex designs to both technical and nontechnical audiences.

Solution Architect Data & AI (GCP + AdTech Focus) Experience : 10+ Years Employment Type: Full Time Role Overview: We are seeking a highly experienced Solution Architect with deep expertise in Google Cloud Platform (GCP) and a proven track record in architecting data and AI solutions for the AdTech industry. This role will be pivotal in designing scalable, real-time, and privacy-compliant solutions for programmatic advertising, customer analytics, and AI-driven personalization. The ideal candidate should blend strong technical architecture capabilities with deep domain expertise in advertising technology and digital marketing ecosystems. Key Responsibilities: Architect and lead GCP-native data and AI solutions tailored to AdTech use cases—such as real-time bidding, campaign analytics, customer segmentation, and look alike modeling. Design high-throughput data pipelines, audience data lakes, and analytics platforms leveraging GCP services like BigQuery, Dataflow, Pub/Sub, Cloud Storage, Vertex AI, etc. Collaborate with ad operations, marketing teams, and digital product owners to understand business goals and translate them into scalable and performant solutions. Integrate with third-party AdTech and MarTech platforms, including DSPs, SSPs, CDPs, DMPs, ad exchanges, and identity resolution systems. Ensure architectural alignment with data privacy regulations (GDPR, CCPA) and support consent management and data anonymization strategies. Drive technical leadership across multi-disciplinary teams (Data Engineering, MLOps, Analytics) and enforce best practices in data governance, model deployment, and cloud optimization. Lead discovery workshops, solution assessments, and architecture reviews during pre-sales and delivery cycles. GCP & AdTech Tech Stack Expertise: BigQuery, Cloud Pub/Sub, Dataflow, Dataproc, Cloud Composer (Airflow), Vertex AI, AI Platform, AutoML, Cloud Functions, Cloud Run, Looker, Apigee, Dataplex, GKE Deep understanding of programmatic advertising (RTB, OpenRTB), cookie-less identity frameworks, and AdTech/MarTech data flows. Experience integrating or building components like: Data Management Platforms (DMPs) Customer Data Platforms (CDPs) Demand-Side Platforms (DSPs) Ad servers, attribution engines, and real-time bidding pipelines Event-driven and microservices architecture using APIs, streaming pipelines, and edge delivery networks. Integration with platforms like Google Marketing Platform, Google Ads Data Hub, Snowplow, Segment, or similar. Strong understanding of IAM, data encryption, PII anonymization, and regulatory compliance (GDPR, CCPA, HIPAA if applicable). Experience with CI/CD pipelines (Cloud Build), Infrastructure as Code (Terraform), and MLOps pipelines using Vertex AI or Kubeflow. Strong experience in Python and SQL; familiarity with Scala or Java is a plus. Experience with version control (Git), Agile delivery, and architectural documentation tools.

As a GCP Architect in this role based in Pune, you will be responsible for working within a DevOps model to design, implement, and maintain access control solutions. Your expertise in Python, SQL, Terraform, and CI/CD pipelines will be essential in ensuring the effective deployment and management of resources on Google Cloud Platform. Your primary focus will be on architecting secure and scalable GCP solutions that meet the organization's requirements and standards. This position offers the opportunity to contribute to the continuous improvement of cloud infrastructure while collaborating with cross-functional teams to drive innovation and efficiency.,

At EY, you'll have the opportunity to shape a career that is as unique as you are, with the global reach, support, inclusive culture, and technological resources needed to realize your full potential. Your individual voice and perspective are crucial in contributing to EY's continuous improvement. Join us in creating an exceptional experience for yourself and contributing to a better working world for all. As the GCP Architect - Manager, your primary responsibility will be to lead a migration project, ensuring a smooth transition of workloads, applications, and services to Google Cloud Platform (GCP) while seamlessly integrating with other cloud environments like AWS and Azure. Your expertise in cloud architecture, security, networking, and automation, along with hands-on experience in large-scale migrations, will be essential for success in this role. Key Responsibilities: - Cloud Strategy & Architecture: Design and implement scalable, secure, and cost-effective GCP architectures for a multi-cloud environment. - Migration Planning: Develop and execute migration strategies for applications, data, and infrastructure from on-premise or other cloud platforms to GCP. - Infrastructure as Code (IaC): Utilize tools like Terraform, Ansible for automated provisioning and management of cloud resources. - Security & Compliance: Ensure adherence to industry security best practices, compliance standards, and Google Cloud security frameworks. - CI/CD & DevOps Integration: Collaborate with DevOps teams to integrate CI/CD pipelines for cloud deployments. - Networking & Hybrid Cloud: Design hybrid and multi-cloud networking solutions, including VPNs, interconnects, and service mesh. - Performance & Cost Optimization: Monitor and optimize cloud resource utilization for cost efficiency and performance enhancements. - Stakeholder Collaboration: Work closely with business, security, and engineering teams to align cloud solutions with organizational goals. - Incident Management & Troubleshooting: Provide technical leadership for incident resolution and continuous improvement in cloud operations. Experience: You should have 7-11 years of relevant experience. Technical Expertise: - Strong hands-on experience with GCP services and familiarity with AWS and Azure services. - Proficiency in Terraform, Ansible, containerization, microservices architecture, and networking. - Understanding of security best practices, encryption, and identity management. - Experience in migration from on-prem to GCP or hybrid cloud architectures. - Proficiency in scripting languages like Python, Bash, or Go for automation. Certifications (Preferred): - Google Professional Cloud Architect - Google Professional Cloud Security Engineer - AWS/Azure Architect certifications (nice to have) Soft Skills: - Excellent problem-solving and analytical skills. - Strong communication and stakeholder management abilities. - Leadership and mentoring skills within a fast-paced environment. Join EY in building a better working world, where data and technology empower diverse teams across 150 countries to provide trust through assurance and drive growth, transformation, and operational excellence for clients. EY's global teams in assurance, consulting, law, strategy, tax, and transactions are committed to asking better questions to address the complex issues of today's world.,

As a GCP Architect with AI Expertise, you will play a crucial role in leading the design, implementation, and optimization of cloud and AI-driven solutions on Google Cloud Platform (GCP). Your deep expertise in cloud infrastructure, AI/ML, networking, and security will be essential for architecting scalable, secure, and highly available cloud solutions while leveraging AI to drive automation and intelligence across enterprise environments. Your responsibilities will include designing and implementing scalable, secure, and cost-effective architectures on GCP, developing AI/ML-driven solutions using tools such as Vertex AI, BigQuery ML, TensorFlow, and AutoML, and architecting end-to-end data pipelines to support AI model training, deployment, and monitoring. You will also be responsible for building high-availability, backup, and disaster recovery solutions in GCP. In terms of infrastructure and security, you will implement identity management, IAM policies, security protocols, and network segmentation, design and automate provisioning of networks, firewalls, ACLs, and access control policies, and ensure compliance with security and governance frameworks for cloud-based AI workloads. Additionally, you will manage multi-VPC networking, hybrid cloud connectivity, and firewall configurations. Your role will also involve leading large-scale application and network migrations to GCP, developing Terraform-based infrastructure automation, and managing Infrastructure as Code (IaC). You will implement CI/CD pipelines for AI/ML workloads using tools like GitHub, Jenkins, and Ansible, and design DevOps solutions with cloud-native tools and containerized workloads on GKE. As a technical leader and advisor, you will provide strategic guidance on cloud adoption, AI/ML use cases, and infrastructure modernization, lead requirements gathering, solution design, and implementation for GCP cloud-based AI solutions, and support pre-sales activities, including POCs, RFP responses, and SOW creation. You will mentor and provide technical oversight to engineering teams and serve as a trusted cloud advisor for customers, helping them solve complex cloud infrastructure and AI challenges. Furthermore, you will be responsible for optimizing cloud resource usage, cost management, and AI model performance, conducting cloud usage analytics, security audits, and AI model monitoring, and developing strategies to improve network reliability, redundancy, and high availability. If you are passionate about cloud transformation, AI, and solving complex infrastructure challenges, this role presents a perfect opportunity for you to make a meaningful impact in the field of cloud and AI technologies.,

Role and Responsibilities: 1. Cloud Architecture Design: Design, implement, and manage robust and scalable cloud architecture solutions on the Google Cloud Platform Collaborate with cross-functional teams to understand business requirements and translate them into secure, efficient, and reliable cloud solutions 2. Infrastructure as Code (IaC): Develop Infrastructure as Code (IaC) scripts using tools such as Terraform to automate the provisioning and configuration of GCP resources Ensure consistency, repeatability, and version control of infrastructure deployments 3. Migration and Integration: Lead and execute cloud migration projects, ensuring seamless transitions from on-premises environments to GCP Integrate GCP services with existing systems and applications, optimizing performance and minimizing downtime 4. Security and Compliance: Implement security best practices and ensure compliance with industry standards and regulations Conduct regular security assessments and audits to identify and address potential vulnerabilities 5. Performance Optimization: Continuously monitor and optimize GCP infrastructure for performance, cost, and reliability Identify and implement improvements to enhance overall system efficiency 6. Collaboration and Documentation: Collaborate with development and operations teams to align cloud solutions with overall business objectives Create and maintain comprehensive documentation for architecture, configurations, and processes 7. Troubleshooting and Support: Provide expert-level support for GCP-related issues, troubleshoot problems, and implement effective solutions Participate in on-call rotation support as needed Additional Qualifications: GCP Professional Architect certification is highly desirable Strong expertise in designing and implementing cloud-native solutions on GCP Proficiency in Infrastructure as Code (IaC) tools, particularly Terraform In-depth knowledge of cloud security best practices and compliance requirements Excellent communication skills and the ability to collaborate effectively with cross-functional teams Strong problem-solving and troubleshooting skills

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.

We are looking for 8+years experienced candidates for this role. Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications : AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD) Primary Skills : Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as vSphere, ESXi, and vCenter. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation. Good understanding of SQL and NoSQL databases. Deep expertise in DevOps practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Secondary Skills : Experience with infrastructure services such as LDAP, DNS, DHCP, and Active Directory. Excellent communication, documentation, and presentation skills. Proficiency in scripting languages such as Python, Bash, or PowerShell for automation tasks.