AWS Cloud Engineer with AI (LLM) | Princeton, NJ | Contract

Overview

On Site
Depends on Experience
Accepts corp to corp applications
Contract - Independent
Contract - W2
Contract - 12 Month(s)

Skills

Amazon DynamoDB
API
Amazon S3
Amazon SQS
Amazon SageMaker
Amazon Web Services
Application Development
Artificial Intelligence
Cloud Computing
Cloud Security
Collaboration
Conflict Resolution
Continuous Delivery
Continuous Integration
Debugging
DevOps
Generative Artificial Intelligence (AI)
Git
Microservices
Network Security
Node.js
Performance Tuning
Problem Solving
Python
Regulatory Compliance
SDK
Step-Functions
Team Building
Workflow

Job Details

Hi ,
Greetings from Healthcare Triangle !!

We do have opening for our client,

Role : AWS Cloud Engineer with AI (LLM)
Location : Princeton , NJ
Duration : Long-term Contract
Job Description:

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 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 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.

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