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Job Title: GCP Platform Engineer – Enterprise Cloud; AI Platform
Location: Lebanon NJ (Hybrid role)
Role Summary:
The GCP Platform Engineer is responsible for designing, building, and operating secure, compliant, and scalable cloud and AI-enabled platforms on Google Cloud Platform (GCP). This role enables application, data, and analytics teams by providing standardized cloud infrastructure, Kubernetes platforms, and approved Google AI services, while meeting financial services regulatory, security, and resiliency requirements.
The engineer partners with the Cloud, Data ; AI teams, Information Security, and Risk to ensure AI workloads are deployed with appropriate governance, data controls, and observability
Key Responsibilities
Enterprise Cloud ; AI Platform
Design and maintain enterprise GCP landing zones aligned with governance standards
Build and operate shared cloud services supporting AI and non-AI workloads
Implement Infrastructure as Code (Terraform) for platform, networking, and AI service enablement
Support hybrid connectivity and secure data access patterns for AI use cases Kubernetes, Containers ; AI Workloads
Engineer and operate GKE clusters for application and AI inference workloads Enable containerized AI services and microservices using approved base images Support GPU-enabled workloads where approved
Implement standardized deployment patterns for AI APIs and services Google AI / GenAI EnablementEnable and operate approved Google AI services, including:
Vertex AI (model hosting, endpoints, pipelines – platform enablement only, agentic AI engine and communication protocols)
Job Title: GCP Platform Engineer – Enterprise Cloud; AI Platform
Location: Lebanon NJ (Hybrid role)
Role Summary:
The GCP Platform Engineer is responsible for designing, building, and operating secure, compliant, and scalable cloud and AI-enabled platforms on Google Cloud Platform (GCP). This role enables application, data, and analytics teams by providing standardized cloud infrastructure, Kubernetes platforms, and approved Google AI services, while meeting financial services regulatory, security, and resiliency requirements.
The engineer partners with the Cloud, Data ; AI teams, Information Security, and Risk to ensure AI workloads are deployed with appropriate governance, data controls, and observability
Key Responsibilities
Enterprise Cloud ; AI Platform
Design and maintain enterprise GCP landing zones aligned with governance standards
Build and operate shared cloud services supporting AI and non-AI workloads
Implement Infrastructure as Code (Terraform) for platform, networking, and AI service enablement
Support hybrid connectivity and secure data access patterns for AI use cases Kubernetes, Containers ; AI Workloads
Engineer and operate GKE clusters for application and AI inference workloads Enable containerized AI services and microservices using approved base images Support GPU-enabled workloads where approved
Implement standardized deployment patterns for AI APIs and services Google AI / GenAI EnablementEnable and operate approved Google AI services, including:
Vertex AI (model hosting, endpoints, pipelines – platform enablement only, agentic AI engine and communication protocols)
Teamwork, quality of life, professional and personal development: values that Virtusa is proud to embody. When you join us, you join a team of 30,000 people globally that cares about your growth — one that seeks to provide you with exciting projects, opportunities and work with state of the art technologies throughout your career with us.
Great minds, great potential: it all comes together at Virtusa. We value collaboration and the team environment of our company, and seek to provide great minds with a dynamic place to nurture new ideas and foster excellence.
Virtusa is an Equal Opportunity Employer. All applicants will receive fair and impartial treatment without regard to race, color, religion, sex, national origin, ancestry, age, legally protected physical or mental disability, protected veteran status, status in the U.S. uniformed services, sexual orientation, gender identity or expression, marital status, genetic information or on any other basis which is protected under applicable federal, state or local law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government-issued ID during each interview. All candidates must be authorized to work in the USA.
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