AI Integration & Development: Design develop and implement AI-powered automation and applications using AWS Bedrock LLMs (Large Language Models) or SageMaker.
Backend Java Engineering: Develop robust backend services and RESTful APIs using Java 17/21 Spring Boot and microservices architecture.
AWS Cloud Native Development: Build scalable resilient solutions utilizing AWS services such as Lambda S3 API Gateway and DynamoDB.
MLOps & Pipeline Management: Implement CI/CD pipelines to automate the deployment monitoring and operational lifecycle of AI models.
Data Handling: Process and clean data to feed machine learning models creating intelligent algorithms to enhance automation.
Collaboration: Work with cross-functional teams (data scientists DevOps) to translate business requirements into technical AI solutions
Top skills required for this role:
Programming: Strong hands-on experience in Java (17 preferred) and Spring Boot.
AI/ML Knowledge: Familiarity with AI/ML frameworks (TensorFlow PyTorch) and experience with generative AI tools (e.g. Bedrock SageMaker).
Infrastructure as Code (IaC): Experience with Terraform or CloudFormation.
Architecture: Understanding of microservices event-driven architectures and RESTful API design.
DevOps: Experience with Docker Kubernetes and Jenkins
Job Title: Java AI Developer Location: New Jersey - NJ / Plano-TX (Onsite) Job Type: Contract Responsibilities: AI Integration & Development: Design develop and implement AI-powered automation and applications using AWS Bedrock LLMs (Large Language Models) or SageMaker. Backend Java Engi...
Job Title: Java AI Developer
Location: New Jersey - NJ / Plano-TX (Onsite)
Job Type: Contract
Responsibilities:
AI Integration & Development: Design develop and implement AI-powered automation and applications using AWS Bedrock LLMs (Large Language Models) or SageMaker.
Backend Java Engineering: Develop robust backend services and RESTful APIs using Java 17/21 Spring Boot and microservices architecture.
AWS Cloud Native Development: Build scalable resilient solutions utilizing AWS services such as Lambda S3 API Gateway and DynamoDB.
MLOps & Pipeline Management: Implement CI/CD pipelines to automate the deployment monitoring and operational lifecycle of AI models.
Data Handling: Process and clean data to feed machine learning models creating intelligent algorithms to enhance automation.
Collaboration: Work with cross-functional teams (data scientists DevOps) to translate business requirements into technical AI solutions
Top skills required for this role:
Programming: Strong hands-on experience in Java (17 preferred) and Spring Boot.