AI Full Stack Developer

Reailize•Brookhaven, GA

10h•Hybrid

About The Position

We are looking for an AI Full Stack Developer to design, build, and deploy intelligent web applications powered by large language models and AI SDKs. You will own features end to end from the user interface and backend services to the LLM-based capabilities that drive them and ship them into production. Note on tech stack: Internally, the applications are built on a MERN stack (MongoDB, Express.js, React, Node.js). Direct experience with this stack to build web based application is a plus, but we're primarily hiring for strong full-stack and AI-building ability the right candidate can ramp on our specific stack quickly. This is a hybrid opportunity where you will be working out of any one of the listed locations 2 days/week.

Requirements

Degree in computer science, AI, data science, or a related field (or equivalent experience).
Strong programming skills, including a primary web-focused language and a language commonly used for AI/ML work.
Direct experience with the MERN stack (MongoDB, Express.js, React, Node.js).
Experience building AI agents or multi-step LLM workflows.
Proven experience building production web applications end to end.
Experience building features on top of large language models and AI SDKs prompt engineering, retrieval, and function/tool use.
Experience building responsive user interfaces and robust backend services and APIs.
Experience designing and integrating APIs and service-oriented architecture.
Familiarity with embeddings, vector retrieval, and retrieval-augmented generation patterns.
Familiarity with containers and automated deployment pipelines.
Understanding of cloud deployment and infrastructure.
Strong understanding of authentication, authorization, and API security.
Comfort with version control and collaborative development workflows.
Strong debugging and problem-solving skills.

Responsibilities

Design, build, and maintain full-stack web applications with AI-powered features.
Build and integrate LLM-based features chat, copilots, summarization, extraction, and retrieval-augmented generation into products.
Do prompt engineering, tool/function calling, and agent workflows on top of AI SDKs.
Design evaluation and guardrail patterns for AI features (quality, safety, cost, latency).
Develop scalable, secure backend services and APIs that wrap AI capabilities.
Create responsive, reusable, maintainable user interfaces for AI features.
Integrate AI SDKs, embedding models, and vector retrieval with internal services.
Deploy applications and AI services to cloud environments.
Set up CI/CD and monitor production AI features for latency, cost, and quality drift.
Troubleshoot issues across the full stack.
Work with product, design, and engineering teams in an Agile environment.
Apply security best practices across applications and AI integrations.