Hybrid
Description:
Senior AI Cloud Engineer
Qualifications
At least ten or more years of experience performing the functions associated with this labor category
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or equivalent work experience.
Proven experience in Generative AI, data engineering, AWS AI, and AWS data services.
Proficiency in programming languages such as Python, Java, or similar.
Experience with data engineering concepts and tools
Experience in Terraform, Dockers, Kubernetes, and/or Gitlab
Understanding of data governance and security principles
Hands-on experience with DevSecOps and CI/CD practices
Excellent problem-solving and analytical skills
Ability to work independently and as part of a team
Familiarity with government cloud deployment regulations/compliance policies such as FedRAMP, FISMA, etc.
Experience with specific generative AI models like GPT, Llama, Claude, and others from HuggingFace
Knowledge of deep learning frameworks such as PyTorch and Transformer
Contributions to open-source AI projects or communities
Certifications in AWS AI or machine learning
Capabilities
Builds next-generation AI & analytics framework developed on a group of core technologies.
Utilize Generative AI techniques to create innovative solutions for business challenges.
AWS AI Services: Leverage AWS AI services like Amazon Bedrock, SageMaker, Comprehend, Rekognition, Transcribe to accelerate AI development and deployment.
Lead multi-functional teams in designing and implementing cloud-based data and AI solutions.
Ensure data pipelines are scalable, secure, and repeatable.
AWS Data Services: Utilize AWS data services like Amazon S3, Amazon Redshift, and Amazon DynamoDB to store, manage, and process large-scale datasets.
Collaborate with stakeholders to understand business requirements and turn data into insights.
Develop and maintain cloud infrastructure, including data lakes, warehouses, and analytics platforms.
Implement data governance and security best practices.
DevSecOps: Contribute to a DevSecOps culture by adhering to standard methodologies for secure software development and deployment.
CI/CD: Automate AI model development, testing, and deployment using CI/CD pipelines.
Acts as an inspiring leader, with an outstanding perspective, and promotes the adoption of new software and technology across the company.
Works on multiple projects as a technical team member driving business requirements end to end
Takes end to end accountability of all data products and solutions.
Conducts training bootcamps and cross-training workshops for internal collaborators and customers.
Certifications
Certifications in AWS AI or Machine Learning
VIVA is an equal opportunity employer. All qualified applicants have an equal opportunity for placement, and all employees have an equal opportunity to develop on the job. This means that VIVA will not discriminate against any employee or qualified applicant on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status