Key Responsibilities
Assess and enhance the AI platforms cloud infrastructure and data pipeline resilience using AWS and cloud based technologies
Ensure scalability and fault tolerance of AI ML models within cloud environments
Identify and resolve bottlenecks in model inference and training pipelines focusing on performance and resource optimization
Optimize cloud resource utilization on AWS for real time use cases including AI model deployment
Collaborate with the DevOps team on improving cloud deployment processes and managing AWS infrastructure
Implement automated testing to simulate fault tolerance and ensure high availability
Provide ongoing technical support for users of the Generative AI platform troubleshooting issues and responding to queries to ensure seamless operations
Monitor cloud platform performance on AWS identifying and implementing optimization strategies to improve cost efficiency and scalability
Work with AWS cloud services eg EC2 S3 Lambda VPC to ensure proper configuration management and performance
Document key processes issues and solutions for knowledge sharing and future reference
Stay updated with industry trends in Generative AI cloud technologies and AWS cloud administration
As a Generative AI Platform Support Engineer you will be responsible for providing technical support for our AI platform focusing on the integration of cloud infrastructure deployment and ongoing maintenance You will work closely with cross functional teams to troubleshoot technical issues implement platform enhancements monitor system performance and ensure the platform runs efficiently and effectively Your role will leverage expertise in AWS Cloud Administration and Infrastructure management to support platform operations and ensure optimal system performance
Key Responsibilities
Assess and enhance the AI platforms cloud infrastructure and data pipeline resilience using AWS and cloud based technologies
Ensure scalability and fault tolerance of AI ML models within cloud environments
Identify and resolve bottlenecks in model inference and training pipelines focusing on performance and resource optimization
Optimize cloud resource utilization on AWS for real time use cases including AI model deployment
Collaborate with the DevOps team on improving cloud deployment processes and managing AWS infrastructure
Implement automated testing to simulate fault tolerance and ensure high availability
Provide ongoing technical support for users of the Generative AI platform troubleshooting issues and responding to queries to ensure seamless operations
Monitor cloud platform performance on AWS identifying and implementing optimization strategies to improve cost efficiency and scalability
Work with AWS cloud services eg EC2 S3 Lambda VPC to ensure proper configuration management and performance
Document key processes issues and solutions for knowledge sharing and future reference
Stay updated with industry trends in Generative AI cloud technologies and AWS cloud administration
Key job details
About Virtusa
Teamwork, quality of life, professional and personal development: values that Virtusa is proud to embody. When you join us, you join a team of 27,000 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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