Enterprise Full Stack Engineer (AWS & GenAI Platform Development)

Locations: Plano, TX Duration: 06 Months with Possible Extension.

Pay Range: $60-$65/Hour on W2/C2C (All inclusive) We are seeking a highly skilled Senior Full Stack Developer to transform an existing prototype into a secure, scalable, and enterprise-grade application deployed on AWS. The ideal candidate will have strong experience across front-end and back-end development, cloud technologies, DevOps, and enterprise application modernization. As part of the initial project, you will help build a modern Learning Experience Platform (LXP) that delivers personalized, engaging, and scalable learning experiences for employees and learners.

Key Responsibilities: Convert prototype applications into production-ready enterprise solutions. Design, develop, test, deploy, and support scalable full-stack applications. Build and maintain cloud-native solutions on AWS. Develop front-end and back-end components using modern technologies. Implement CI/CD pipelines and Infrastructure as Code (Terraform). Deploy and manage applications using Docker and Kubernetes. Integrate enterprise authentication, authorization, and security controls. Implement automated testing across UI and backend layers. Establish observability practices, including logging, monitoring, and alerting. Collaborate with product, design, engineering, content, and analytics teams. Support production deployments, troubleshooting, and operational handoff. Document technical solutions, architecture, and support procedures.

Required Skills: Strong Full Stack Development experience. AWS services such as S3, Lambda, and Bedrock. Docker and Kubernetes. Terraform and Infrastructure as Code. CI/CD pipeline implementation. Enterprise Security, Authentication, and IAM. Automated Testing and Quality Assurance. Git/GitHub for version control and collaboration. Monitoring, Logging, and Alerting tools. Excellent communication and problem-solving skills.

Preferred: SkillsGitHub Copilot, Claude Code, or Kiro. Generative AI technologies and concepts: RAG (Retrieval-Augmented Generation) Vector Databases & Embeddings LLMs and Prompt Engineering Agentic Frameworks MCP (Model Context Protocol) Model Fine-tuning AI Guardrails and Evaluations MLOps practices. Experience modernizing enterprise applications. Experience supporting production systems in large enterprise environments.

Experience: Required 8 years of Full Stack Development experience. Experience with AWS cloud-native application development. Experience building and deploying enterprise-scale applications.