AWS Cloud Developer with AI (LLM)

? - Featured Role | Apply direct with Data Freelance HubThis role is for an AWS Cloud Developer with AI (LLM) for a contract position in Princeton, NJ. Requires 8-12 years of AWS experience, proficiency in Node.js/Python, and expertise in serverless services and AI features using Amazon Bedrock or SageMaker.United States$ USDMarch 10, 2026On-sitePrinceton, NJMonitoring #DynamoDB #S3 (Amazon Simple Storage Service) #AWS (Amazon Web Services) #Cloud #API (Application Programming Interface) #SQS (Simple Queue Service) #Compliance #Microservices #Python #SNS (Simple Notification Service) #Scala #DevOps #AI (Artificial Intelligence) #SageMaker #GIT #Programming #Infrastructure as Code (IaC) #Lambda (AWS Lambda) #Deployment #Observability #Logging #Code Reviews #Security #Automation #DebuggingJob Summary AWS Cloud Developer with AI (LLM) Divergent Talent Contract In-Office | Princeton, NJ, United States To succeed, this Role's Responsibilities Would Involve: Bring a developer's mindset with strong knowledge of AWS cloud engineering. Be comfortable building, debugging, and enhancing serverless applications. Work collaboratively with architects, product teams, and DevOps to deliver end-to-end solutions. Understand modern cloud design principles, security practices, and automation standards. Stay current with evolving AWS services and Generative AI capabilities. Responsibilities: Application Development & Integration: Build and enhance cloud-native applications using AWS services such as Lambda, API Gateway, DynamoDB, SQS/SNS, Step Functions, and S3. Develop AI-enabled features using LLMs, Agentic AI, and AWS services like Amazon Bedrock and SageMaker. Write clean, maintainable, secure, and testable code using Node.js or Python. Implement event-driven workflows, asynchronous integrations, and serverless APIs. Integrate AWS services programmatically using AWS SDK. Cloud Engineering & Infra Automation: Implement Infrastructure-as-Code (IaC) using CloudFormation. Contribute to CI/CD pipelines using AWS Code Pipeline, Code Build, and Code Deploy. Support observability by configuring logging, monitoring, tracing, and alerts. Follow cloud security, compliance, and operational best practices. AI/LLM Feature Implementation: Build LLM-driven features, inference workflows, prompt-handling, and agent-based automation using Bedrock. Develop scalable AI components and integrate them into backend services. Experiment with new AWS AI capabilities and contribute to PoCs. Collaboration & Delivery: Work with architects and senior engineers to translate high-level architecture into implementation. Participate in code reviews, design discussions, and team development practices. Troubleshoot issues, optimize application performance, and support deployment activities. Mandatory Skills: 8 to 12 years of overall experience with strong AWS development background. Hands-on development using AWS serverless services: Lambda, DynamoDB, SNS/SQS, Step Functions, API Gateway. Experience developing AI/LLM features using Amazon Bedrock or SageMaker. Strong programming experience in Node.js or Python. Solid experience with AWS SDK, event-driven patterns, and microservices. Good understanding of AWS compute, networking, security, and CI/CD. Experience with CloudFormation for IaC. Experience with Git and modern development workflows. Strong debugging, problem-solving, and performance optimization skills. Ability to write secure, scalable, production-grade cloud applications.Freelance data hiring powered by an engaged, trusted community — not a CV database.J-18808-Ljbffr