Fullstack AI Engineer

Jobtailor; Dallas (TX); On-site; USD 120,000 - 160,000; Full time

Job summary

Jobtailor is seeking a seasoned full‑stack engineer to design and deliver AI‑powered applications in cloud environments, with a focus on scalable front‑end and robust back‑end systems.

You will integrate LLMs and retrieval‑augmented generation, build RESTful/GraphQL APIs, and deploy on AWS/GCP/Azure, ensuring security and high performance in production.

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, or a related field (or equivalent experience).
• 4+ years of experience in full‑stack development, with a track record of building scalable, production‑ready systems.
• Strong proficiency in JavaScript/TypeScript, Python, and modern front‑end frameworks (React, Vue, or Angular).
• Experience with agentic frameworks such as LangChain, AutoGen or CrewAI.
• Hands‑on experience with integrating AI models via APIs (OpenAI, Hugging Face, etc.).
• Knowledge of vector databases, embeddings, and retrieval‑augmented generation (RAG) techniques.
• Experience with cloud platforms (e.g., AWS, Azure, GCP), containerization (Docker, Kubernetes), and CI/CD pipelines.
• Strong understanding of database technologies (SQL, NoSQL, Firebase, MongoDB, PostgreSQL).
• Ability to design scalable and maintainable architectures for AI‑driven applications.
• Capable of working closely with cross‑functional teams to deliver cohesive, end‑to‑end functionality.
• Knowledge of message queues (e.g., RabbitMQ, Kafka) and caching systems (e.g., Redis).

Responsibilities

• Develop and implement end-to-end AI-driven applications, integrating generative AI models
• Build and maintain scalable front‑end interfaces using modern web frameworks (React, Angular, Vue.js)
• Design and develop robust back‑end services using Node.js, Python, or other back‑end technologies
• Integrate large language models (LLMs) and multimodal AI models into applications
• Optimize application performance, ensuring efficiency in AI inference and API response times
• Develop and maintain RESTful and GraphQL APIs for AI model interaction
• Deploy AI applications on cloud platforms (AWS, GCP, Azure) using containerization and serverless technologies
• Ensure security, scalability, and compliance of AI-driven applications
• Stay up to date with the latest advancements in Generative/Agentic AI, web development, and cloud technologies

Skills

Full-stack

JavaScript/TypeScript

Python

React/Vue/Angular

LangChain

AutoGen

API Integration

Vector Databases

Cloud Platforms

Docker/Kubernetes

Education

Bachelor's degree in Computer Science or related field

Tools

React

Vue.js

Angular

Node.js

Docker

Kubernetes

Git

PostgreSQL

MongoDB

Firebase

Job description

Responsibilities

• Develop and implement end-to-end AI-driven applications, integrating generative AI models
• Build and maintain scalable front‑end interfaces using modern web frameworks (React, Angular, Vue.js)
• Design and develop robust back‑end services using Node.js, Python, or other back‑end technologies
• Integrate large language models (LLMs) and multimodal AI models into applications
• Optimize application performance, ensuring efficiency in AI inference and API response times
• Develop and maintain RESTful and GraphQL APIs for AI model interaction
• Deploy AI applications on cloud platforms (AWS, GCP, Azure) using containerization and serverless technologies
• Ensure security, scalability, and compliance of AI-driven applications
• Stay up to date with the latest advancements in Generative/Agentic AI, web development, and cloud technologies

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, or a related field (or equivalent experience)
• 4+ years of experience in full‑stack development, with a track record of building scalable, production‑ready systems
• Strong proficiency in JavaScript/TypeScript, Python, and modern front‑end frameworks (React, Vue, or Angular)
• Experience with agentic frameworks such as LangChain, AutoGen or CrewAI
• Hands‑on experience with integrating AI models via APIs (OpenAI, Hugging Face, etc.)
• Knowledge of vector databases, embeddings, and retrieval‑augmented generation (RAG) techniques
• Experience with cloud platforms (e.g., AWS, Azure, GCP), containerization (Docker, Kubernetes), and CI/CD pipelines
• Strong understanding of database technologies (SQL, NoSQL, Firebase, MongoDB, PostgreSQL)
• Ability to design scalable and maintainable architectures for AI-driven applications
• Capable of working closely with cross‑functional teams to deliver cohesive, end‑to‑end functionality
• Knowledge of message queues (e.g., RabbitMQ, Kafka) and caching systems (e.g., Redis)