Full-Stack Software
18 hours ago
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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