Full-Stack Generative AI Developer

Overview

Design, implement, and maintain cutting-edge AI-powered applications and services. Bridge advanced generative AI models with user-facing applications. Build intuitive interfaces for complex AI capabilities. Develop robust, scalable, and efficient backend systems.

AI Development

• Design and implement generative AI features using foundational models such as GPT-5, Llama, and other Large Language Models (LLMs)
• Fine-tune and optimize AI models for specific use cases and domains — optional/good to have
• Create prompt engineering frameworks and templates to ensure consistent AI behavior
• Develop Retrieval-Augmented Generation (RAG) systems combining vector databases with LLMs
• Demonstrate working knowledge of LLM evaluation and observability platforms
• Apply AI technologies to build scalable, production-ready solutions

Frontend Development — Basic Exposure

• Build responsive and accessible web interfaces for AI-powered applications
• Experience with modern frontend frameworks such as React, Vue, Angular, MUI
• Design intuitive user interfaces that make complex AI capabilities easy to understand and use
• Implement real-time AI interaction features, including streaming responses and progressive rendering
• Develop visualization components for AI outputs, confidence metrics, and AI-generated insights

Backend Development

• Create robust APIs and services using Python and similar frameworks
• Develop APIs to interface with AI models, external services, and enterprise applications
• Design scalable architectures capable of supporting high-throughput AI inference
• Implement efficient data processing pipelines for AI training and AI inference
• Integrate with vector databases, document stores, and AI-specific infrastructure

DevOps & MLOps

• Set up and maintain CI/CD pipelines for AI application deployment
• Implement monitoring, logging, and alerting for AI systems
• Optimize infrastructure for cost-effective AI deployment
• Support containerized AI applications using Docker and Kubernetes
• Implement cloud-based deployment solutions using AWS, Azure, or GCP

Required Technical Skills

• 3+ years of full-stack development experience
• Strong programming experience with JavaScript, TypeScript, and Python — Must Have
• 1+ years of experience working with AI/ML technologies, particularly Generative AI
• Experience with at least one major LLM framework: LangChain or LangGraph
• Proficiency with vector databases such as Pinecone, MongoDB, or FAISS
• Strong understanding of REST APIs (GraphQL — optional/good to have; Microservices architecture — optional/good to have)
• Experience with Git, GitHub Actions, cloud platforms, Docker, and Kubernetes

AI-Specific Knowledge

• Deep understanding of Large Language Models (LLMs), including their capabilities and limitations
• Strong experience with prompt engineering, RAG architecture, vector databases, embedding models, and vector similarity search
• Understanding of AI evaluation metrics and testing methodologies
• Knowledge of LLM evaluation and observability practices

Preferred Qualifications

• Experience developing commercial AI applications or products
• Knowledge of AI safety and responsible AI deployment practices
• Background in NLP, Computer Vision, or other AI specialties
• Experience with streaming architectures for real-time AI applications
• Experience deploying Generative AI solutions in production environments

Education & Certifications

• Bachelor's degree or higher in Computer Science, Software Engineering, Artificial Intelligence/Machine Learning, or related technical field
• Relevant certifications in cloud platforms, AI frameworks, or software development

Personal Attributes

• Strong problem-solving skills with a creative approach to AI challenges
• Excellent communication skills and ability to explain complex AI concepts to stakeholders
• Ability to stay current with rapidly evolving AI technologies and best practices
• Self-motivated and capable of working independently
• Strong ability to collaborate within cross-functional teams
• Keen interest in the ethical implications of AI technology

Desirable Skills

• Azure Data Factory
• Databricks
• Azure Synapse Analytics
• Python
• SQL
• PySpark
• Databricks

Keywords

• Azure Data Factory
• Databricks
• Azure Synapse Analytics
• Python
• SQL
• PySpark
• Databricks
• Generative AI
• LLM
• RAG
• LangChain
• LangGraph
• Vector Databases
• Prompt Engineering

Essential Skill

Full-Stack Generative AI Development — Design, implement, and maintain AI-powered applications and services. Build scalable backend systems and intuitive user interfaces for Generative AI applications. Integrate foundational models, RAG architectures, vector databases, and AI-specific infrastructure.