Full Stack Generative AI Developer

Overview

We are seeking a talented Full Stack Generative AI Developer to design, develop, and maintain cutting-edge AI-powered applications. The ideal candidate will bridge the gap between advanced Generative AI models and user-facing applications by building scalable, secure, and high-performance AI solutions.

Key Responsibilities

1. Generative AI Development

• Design and develop Generative AI applications using GPT-5, Llama, and other Foundation Models.
• Build Retrieval-Augmented Generation (RAG) solutions integrating LLMs with vector databases.
• Develop prompt engineering frameworks and reusable prompt templates.
• Fine-tune and optimize AI models for domain-specific use cases (Good to have).
• Implement LLM evaluation, observability, and monitoring mechanisms.

2. Frontend Development

• Build responsive AI-powered web applications using React, Vue, Angular, or Material UI.
• Design intuitive and user-friendly interfaces for AI applications.
• Develop streaming AI response interfaces and real-time user interactions.
• Create visualization components for AI outputs, confidence scores, and analytics.

3. Backend Development

• Develop scalable backend services using Python (Mandatory).
• Build REST APIs and GraphQL services for AI applications.
• Design microservices-based architectures.
• Develop high-performance data processing pipelines for AI inference and training.
• Integrate AI services with vector databases, document stores, and enterprise applications.

4. DevOps & MLOps

• Develop CI/CD pipelines for AI application deployment.
• Implement monitoring, logging, and alerting for AI workloads.
• Optimize infrastructure for scalable and cost-effective AI deployment.
• Containerize applications using Docker and Kubernetes.
• Deploy AI solutions on AWS, Azure, or Google Cloud Platform.

Required Skills & Experience

Technical Skills

• 3+ years of Full Stack Development experience.
• Strong programming skills in Python (Mandatory) and JavaScript/TypeScript.
• 1+ years of experience in AI/ML with emphasis on Generative AI.
• Experience with LangChain, LangGraph, or similar LLM frameworks.
• Hands-on experience with Vector Databases such as Pinecone, FAISS, MongoDB, ChromaDB, or Milvus.
• Experience developing REST APIs and GraphQL services.
• Knowledge of Microservices Architecture.
• Experience with Git, GitHub Actions, and CI/CD pipelines.
• Experience with AWS, Azure, or Google Cloud Platform.
• Experience with Docker and Kubernetes.

AI-Specific Knowledge

• Strong understanding of Large Language Models (LLMs) and Foundation Models.
• Experience with Prompt Engineering.
• Hands-on experience building RAG architectures.
• Knowledge of Embedding Models and Vector Similarity Search.
• Understanding of AI evaluation methodologies and model performance metrics.
• Familiarity with AI observability and monitoring tools.

Preferred Qualifications

• Experience fine-tuning LLMs.
• Exposure to AI Agents and Agentic AI frameworks.
• Experience with MLOps pipelines.
• Familiarity with model deployment and inference optimization.
• Strong debugging and problem-solving skills.
• Excellent communication and collaboration skills.