

Hope Tech
AWS Cloud Developer with AI (LLM)
β - Featured Role | Apply direct with Data Freelance Hub
This 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.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
520
-
ποΈ - Date
March 10, 2026
π - Duration
Unknown
-
ποΈ - Location
On-site
-
π - Contract
Unknown
-
π - Security
Unknown
-
π - Location detailed
Princeton, NJ
-
π§ - Skills detailed
#Monitoring #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 #Debugging
Role description
Job 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.
#Workwolf
Job 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.
#Workwolf






