Senior AI Cloud Engineer

Ampcus Inc.•Washington, DC

1d•Onsite

About The Position

Ampcus Inc. is a certified global provider of a broad range of Technology and Business consulting services. We are in search of a highly motivated candidate to join our talented Team.

Requirements

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.

Nice To Haves

Experience with specific generative AI models like GPT, Llama, Claude, and others from Hugging Face.
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

Responsibilities

Builds next-generation AI & analytics framework developed on a group of core technologies.
Utilize Generative AI techniques to create innovative solutions for business challenges.
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.
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.
Contribute to a DevSecOps culture by adhering to standard methodologies for secure software development and deployment.
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 boot camps and cross-training workshops for internal collaborators and customers.