Full Stack Engineer :: Hybrid , Atlanta, GA

Title             : Full Stack Engineer

Location      : Hybrid role - Atlanta, GA

Duration       : 6 months Contract to hire

Interview      : Virtual

Job description:

Enterprise AI Integration (AWS Bedrock or Vertex etc): Integrate LLMs into our platform using Amazon Bedrock or Vertex.

Strong on AWS

Agents build

AI Agents

Architecure

Job Title: Senior Software engineer

We are looking for a pragmatic, high-output Senior Engineer to help revolutionize our technology ecosystem. You will build intelligent systems that serve thousands of internal users, removing manual friction through agentic workflows and high-level AI orchestration.

What You Will Do

• Platform & App Development: Architect, build, and scale end-to-end applications. You will take ownership of major platform features, ensuring they are performant, scalable, and resilient.
• Frontend Engineering: Build responsive, highly interactive, and accessible user interfaces. You will manage complex global state and optimize frontend performance.
• Backend Engineering: Design and implement robust RESTful and GraphQL APIs. You will architect microservices or modular monoliths that can handle high-throughput enterprise traffic.
• Modern DevOps & CI/CD: Design and maintain automated CI/CD pipelines. You will enforce strict automated testing, containerization, and deployment strategies (Blue/Green, Canary) to ensure AI-assisted code is safely tested and deployed.
• Enterprise AI Integration (AWS Bedrock or Vertex etc): Integrate LLMs into our platform using Amazon Bedrock or Vertex. You will build highly secure RAG pipelines, manage vector databases, and implement AI features that directly drive user value.
• AI-Assisted Engineering: Utilize tools like Cursor or GitHub Copilot to accelerate the generation of boilerplate and standard logic, while focusing your human effort on platform architecture, code review, and system design.

Technical Stack Requirements

To be successful in this role, you should have hands-on, production-level experience with the following technologies:

• Frontend: TypeScript, React, Next.js, and modern CSS frameworks (e.g., Tailwind CSS).
• Backend: Node.js (Express/NestJS) and/or Python (FastAPI/Django).
• Databases: Relational databases (PostgreSQL/AWS Aurora) and Vector Data Stores (Amazon OpenSearch Serverless, pgvector, or Pinecone).
• Cloud Infrastructure (AWS or Google Cloud Platform): Deep familiarity with AWS services (Lambda,

ECS/EKS, S3, API Gateway) and Infrastructure as Code (Terraform or AWS

CDK).Cloud Infrastructure (AWS or Google Cloud Platform): Deep familiarity with AWS services

(Lambda, ECS/EKS, S3, API Gateway, DynamoDB) and Google Cloud Platform services (Cloud

Functions, GKE, Cloud Storage, Cloud Pub/Sub), and Infrastructure as Code (Terraform or AWS CDK/Google Cloud Platform Deployment Manager).

AI & Orchestration: Amazon Bedrock (interacting with Foundation Models like Claude or Llama), Google Vertex AI, LangChain/LlamaIndex, and RAG architectures.

• DevOps & CI/CD: Docker, GitLab CI, and observability tools (Datadog, AWS CloudWatch, Google Cloud Monitoring, Google Cloud Logging).
• Testing: Automated testing frameworks across the stack (Jest, PyTest, Playwright, or Cypress).
• Developer Tools: Advanced proficiency with AI coding assistants (Cursor, GitLab Duo, Claude Code).

What We’re Looking For

• Experience: 5+ years of full-stack engineering experience, with a demonstrated history of building and scaling comprehensive web applications or SaaS platforms.
• Quality & Architecture Focus: You view AI as an accelerator, not a replacement for good design. You possess the ability to review and refactor code rigorously, ensuring maintainability and preventing technical debt.
• DevOps Mindset: You don't just write code; you know how to safely deploy, monitor, and maintain it in a cloud-native environment.

Good to Have

• Experience establishing developer platforms or internal tooling to improve team velocity.
• Background in advanced cloud security and IAM role management.
• AWS Certifications (e.g., AWS Certified Developer, DevOps Engineer, or Machine Learning Specialty).