About the company
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AWS Cloud AI Engineer based in United States.
Responsibilities
The AWS Cloud AI Engineer will design, build, and operate secure, scalable AI and machine learning platforms within a modern cloud environment.
- Design, implement, and manage secure, scalable AI and machine learning platforms using AWS cloud technologies.
- Serve as a subject matter expert in AWS infrastructure optimization, applying Infrastructure as Code (IaC) practices to support highly available AI environments.
- Operationalize modern AI and Generative AI workloads, including large language model (LLM) applications, retrieval-augmented generation (RAG), and agent-based AI frameworks.
- Build and maintain cost-efficient cloud platforms using AWS-native services and automated CI/CD pipelines.
- Develop infrastructure solutions supporting AI services such as Amazon Bedrock, SageMaker, Kendra, and related AI capabilities.
- Implement monitoring, observability, and troubleshooting processes to ensure the reliability and performance of AI platforms.
- Create and maintain cloud automation, deployment workflows, and operational documentation.
- Collaborate with data scientists, developers, security teams, and platform engineers to move AI solutions from development into production.
- Integrate security, compliance, and governance controls into AI infrastructure and delivery pipelines.
- Support cloud modernization initiatives, including enterprise architecture improvements and workload migration strategies.
- Manage containerized AI applications using technologies such as Docker and Amazon EKS.
- Improve platform reliability through automation, proactive monitoring, and continuous optimization.
Requirements
The ideal candidate is an experienced cloud and AI engineer with strong knowledge of AWS architecture, machine learning operations, and enterprise-scale technology environments.
- Bachelor’s degree in Computer Science, Engineering, or a related technical discipline, with 5+ years of experience in IT systems engineering or equivalent professional experience.
- Proven experience designing, deploying, and supporting AI-driven workloads using AWS services such as Amazon SageMaker and Amazon Bedrock.
- Strong expertise in AWS foundational services including S3, EC2, RDS, VPC, KMS, and SNS.
- Experience developing and supporting Generative AI solutions using large language models, foundation models, and prompt engineering techniques.
- Knowledge of Retrieval-Augmented Generation (RAG), vector search solutions, and agentic AI workflows.
- Proficiency with Python-based machine learning frameworks such as Hugging Face, PyTorch, or TensorFlow.
- Hands-on experience with Infrastructure as Code tools such as Terraform or CloudFormation.
- Experience designing and managing CI/CD pipelines using tools such as GitHub Actions or AWS CodePipeline.
- Familiarity with cloud security, governance frameworks, compliance requirements, and regulated environments.
- Experience with containerization and orchestration technologies including Docker and Amazon EKS.
- Knowledge of monitoring and observability tools such as Amazon CloudWatch and CloudTrail.
- Ability to collaborate effectively with cross-functional teams and communicate complex technical concepts clearly.
- Strong analytical, troubleshooting, and problem-solving skills with a focus on automation and continuous improvement.
- Experience working in Agile environments and using tools such as Jira and Confluence.
- AWS certifications related to machine learning or Generative AI are preferred.
- Experience in healthcare or other highly regulated industries is a plus.
Conditions
- Competitive salary range of approximately $89,500 to $130,000 annually, depending on experience, qualifications, location, and market factors.
- Comprehensive medical, dental, vision, and pharmacy benefits.
- Retirement savings plan with employer contribution opportunities.
- Flexible Spending Accounts and wellness resources to support employee well-being.
- Paid time off and additional leave programs.
- Opportunities for career advancement, professional development, and technical growth.
- Exposure to innovative AI, cloud, and healthcare technology initiatives.
- Supportive and collaborative work environment focused on meaningful impact.
- Additional compensation opportunities, including discretionary bonuses and merit-based increases.