Full-Stack Software

5 days ago

SAS Nagar, India Lytegen Full time

ROLE: Full Stack Developer (AI Integration + Module Training Specialist)Mission


This person should be able to design, develop, and deploy full-stack applications with integrated AI models and custom training modules, connecting data pipelines and front-end interfaces with intelligence baked in.

Core Responsibilities

1. Full Stack Development (End-to-End)

Architect and develop scalable applications using Python / React / / / Express / MongoDB / PostgreSQL.

Handle both frontend and backend development — UI, APIs, and database logic.

Ensure clean code, modular structure, and reusable components.

2. AI Integration & Model Handling

Integrate OpenAI API, LangChain,, or custom AI APIs for NLP, image, or data analysis use cases.

Create custom training modules where the AI can learn from structured datasets (CSV, text, PDFs, or user inputs).

Implement vector databases (like Pinecone, Weaviate, FAISS) for contextual recall and AI memory.

Fine-tune existing models for internal use (chatbots, content generation, recommendation systems, etc.).

3. Automation & API Orchestration

Set up backend pipelines using Python / Node for automation tasks.

Use Zapier, Make (Integromat), or custom webhooks to connect third-party apps and tools.

Build data ingestion workflows that can pull, clean, and push data for AI consumption.

4. Cloud Deployment & Maintenance

Deploy and manage applications on AWS / Vercel / Render / GCP.

Set up CI/CD pipelines, environment variables, error monitoring, and logging.

Ensure fast response times, uptime stability, and version control via Git/GitHub.

5. Frontend + AI UX Integration

Build clean, intuitive dashboards to visualize AI responses, metrics, or training data.

Implement real-time updates (Sockets / Webhooks) for interactive interfaces.

Focus on user experience when interacting with AI modules — simplicity + clarity.

Required Skill Stack Category

Tools / Knowledge

Frontend

, , Tailwind, Redux, Zustand

Backend

, , RESTful APIs

Databases

MongoDB, PostgreSQL, Firebase, Vector DBs

AI Tools

OpenAI API, LangChain, Hugging Face, Pinecone

Scripting

Python (for data handling + AI API usage)

Cloud

AWS, GCP, Vercel, Render

DevOps

Git, Docker, CI/CD basics

Bonus

Knows prompt engineering, embeddings, and retrieval-based AI architecture

Ideal Background

5+ years of full stack experience with proven AI integration or automation projects.

Built or contributed to a real AI app, chatbot, or SaaS product.

Understands both coding logic and data structure for AI use cases.

Has a product mindset — focuses on usability and scalability, not just "getting it to work."

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