Pay Range: $55hr - $60hr
The Fullstack AWS AI Engineer will be responsible for designing, developing, and deploying cloud-native AI solutions using AWS services and Generative AI technologies. The role involves building scalable AI pipelines, integrating foundation models and LLMs, implementing DevOps and security best practices, and supporting production-grade enterprise applications.
Requirement/Must Have:
Strong experience in full-stack development including front-end and back-end technologies.
Hands-on expertise with AWS cloud services and cloud-native architectures.
Experience building or integrating Agentic or Generative AI solutions.
Proficiency in at least one backend programming language, preferably Python.
Experience with REST APIs, microservices, and asynchronous processing.
Experience with containerization technologies such as Docker and orchestration platforms including ECS and EKS.
Strong understanding of software design patterns, scalability, and system resilience.
Experience working in Agile and DevOps environments.
Experience:
Experience designing and deploying AI solutions using AWS AI services including SageMaker, Bedrock, Rekognition, Textract, Transcribe, and Translate.
Experience integrating foundation models and large language models into enterprise applications.
Experience building AI pipelines for inference, orchestration, fine-tuning, and evaluation.
Experience implementing Infrastructure as Code using CloudFormation, CDK, or Terraform.
Experience developing CI/CD pipelines using GitHub Actions, AWS CodePipeline, or similar tools.
Experience supporting monitoring, logging, troubleshooting, and production operations.
Experience implementing cloud security and compliance best practices.
Responsibilities:
Design, develop, and deploy Agentic and Generative AI solutions using AWS services.
Integrate foundation models and LLMs into enterprise applications.
Build AI pipelines for prompt orchestration, inference, fine-tuning, and evaluation.
Implement responsible AI practices including governance, explainability, and bias mitigation.
Architect and deploy cloud-native applications using AWS core services.
Develop Infrastructure as Code solutions using Terraform, CDK, or CloudFormation.
Design and maintain CI/CD pipelines for automated deployment and testing.
Optimize application performance, scalability, availability, and cloud cost.
Enforce AWS security best practices including IAM, encryption, and VPC configuration.
Implement monitoring and alerting using CloudWatch, X-Ray, and OpenSearch.
Support compliance and governance requirements.
Participate in production support, troubleshooting, and performance tuning activities.
Should Have:
Experience with AWS Well-Architected Framework principles.
Familiarity with SOC2, ISO, or financial services compliance requirements.
Strong understanding of responsible AI and model governance concepts.
Experience building enterprise-scale AI platforms and services.
Skills:
AWS Cloud Services.
Generative AI and Agentic AI solutions.
Amazon Bedrock and SageMaker.
Python and backend development.
REST APIs and microservices.
Docker, ECS, and EKS.
CI/CD pipeline development.
Infrastructure as Code (Terraform, CDK, CloudFormation).
Cloud security and compliance.
Monitoring and logging tools.
Full-stack application development.
Qualification And Education:
Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field preferred.
Equivalent professional experience accepted.