AI-Integrated Full-Stack Engineer

Job description

At Codiora Tech, we build scalable, intelligent software solutions and AI-driven platforms for modern businesses. As an AI-Integrated Full-Stack Engineer, you will operate at the intersection of modern full-stack web architecture, Machine Learning pipelines, and Large Language Models (LLMs). You will design scalable web applications, build robust Python/Node backend microservices, and integrate AI/ML models (OpenAI, Gemini, Claude, custom ML pipelines, vector DBs) into real-world SaaS products. Position level: Mid to Senior. Employment type: Full-Time (Hybrid / On-site). Department: Engineering & AI Labs.

Responsibilities

• Full-Stack Application Development: architect, build, and maintain high-performance web applications using Next.js, React, Node.js, and Express.js
• Python & AI/ML Microservices: develop and optimize Machine Learning microservices using Python (FastAPI / Flask / PyTorch / Scikit-Learn)
• AI & LLM Integration: connect and fine-tune generative AI models and custom LLM APIs (OpenAI, Gemini, Claude, DeepSeek), and build RAG pipelines or workflow automation engines
• Database & API Architecture: design efficient database schemas using PostgreSQL, MongoDB, and Prisma ORM with a focus on high query performance and vector search
• Automation & Data Extraction: develop custom web scrapers, data pipelines, and automation bots to ingest structured data for ML model training and workflows
• DevOps & Deployment: containerize applications using Docker, set up CI/CD pipelines, and manage cloud hosting environments (AWS / Vercel / Render)

Requirements

• Frontend: strong expertise in Next.js, React, TypeScript, Tailwind CSS, and modern UI/UX practices
• Backend & Programming: advanced proficiency in Python (FastAPI/Flask) and JavaScript/TypeScript (Node.js, Express.js, REST APIs, WebSockets)
• AI / ML Core: practical experience with Machine Learning fundamentals, model fine-tuning, prompt engineering, LLM APIs, and vector DBs (ChromaDB, Pinecone, PGVector)
• AI Frameworks: familiarity with LangChain, LlamaIndex, PyTorch, or Scikit-Learn for AI workflow implementation
• Database & DevOps: hands-on experience with PostgreSQL, Prisma ORM, Redis, Docker, Git, and Linux environments
• Nice to have: advanced Retrieval-Augmented Generation (RAG) architecture experience
• Nice to have: familiarity with MLOps frameworks (MLflow, Weights & Biases) or model deployment pipelines
• Nice to have: familiarity with web automation tools (Puppeteer, Playwright, or Selenium)

Benefits

• Competitive salary package based on skills and performance
• Hands-on exposure to next-generation AI/ML projects and SaaS application development
• Collaborative and modern engineering culture with continuous learning opportunities
• Performance-based bonuses and career growth tracks

Skills

• Docker
• FastAPI
• LLM APIs
• Next.js
• Node.js
• PostgreSQL
• Python
• React
• TypeScript