Full Stack AI Developer - #34836

As a Full Stack AI Developer, you will build and deliver intelligent, AI-powered applications that bridge modern web development and advanced AI technologies. You will work across the full stack to integrate, optimize, and deploy AI solutions that solve real-world problems and scale in production environments.

Company Profile:

Our client is a US-based company that builds enterprise-grade, AI-powered marketing systems that help businesses grow online. By automating and optimizing digital marketing campaigns, they deliver strategies that once required large teams and six-figure budgets now accessible at a fraction of the cost.

The company focuses on driving measurable results such as increased leads, traffic, and sales, enabling clients to scale without the need for large in-house marketing teams.

This is a great opportunity for a Full Stack AI Developer to join a collaborative, growth-focused culture where impact matters, communication is open, and continuous learning is part of everyday work.

Duties and Responsibilities:

• Architect & Implement: Develop and maintain robust, scalable full-stack applications with AI at their core
• AI Integration: Use modern AI development tools and APIs (such as OpenAI, LangChain, or Pinecone) to build intelligent features
• Code Mastery: Maintain high standards of code quality through GitHub, participating in rigorous code reviews and collaborative version control
• Innovate: Collaborate with cross-functional teams to brainstorm, prototype, and deploy new AI-driven products
• Optimize: Refine existing projects to improve performance, responsiveness, and AI accuracy

Requirements:
• At least 3 years of experience in Full Stack AI Development
• Technical Versatility: Strong proficiency in both front-end (e.g., React, Vue, or Next.js) and back-end (e.g., Node.js, Python, or Go) technologies
• AI Tooling: Hands-on experience with AI development frameworks and a deep understanding of how to integrate Large Language Models (LLMs) into production environments
• GitHub Fluency: Expert-level comfort with Git workflows, including branching, merging, and collaborative code editing
• Problem Solver: A natural curiosity for solving complex technical puzzles and the ability to learn new tools quickly
• Communication: The ability to explain technical AI concepts to non-technical stakeholders

Advantageous skills or nice-to-haves:

• Experience with vector databases and prompt engineering.
• Knowledge of DevOps and deploying AI models to cloud environments (AWS, Azure, or GCP).
• A portfolio of personal AI projects or open-source contributions.