Lead Full Stack GenAI Developer

Our client is building an AI Centre of Excellence focused on delivering enterprise-scale AI solutions that transform business operations. They are seeking a Lead Full Stack GenAI Developer who is passionate about building production-ready Generative AI applications from architecture through deployment.

This is a highly technical, hands‑on engineering role. The successful candidate will take solution designs and build scalable, secure, enterprise‑grade AI applications that solve real business problems. You’ll work closely with architects, business stakeholders, and cross‑functional teams to deliver end‑to‑end AI solutions that can be reused across the organization.

• Design, develop, and deploy enterprise‑grade Generative AI applications using the Microsoft Azure AI ecosystem.
• Build scalable, reusable backend services and APIs using Python and object‑oriented programming principles.
• Develop modern, responsive frontend applications using React and Type Script.
• Design and implement Retrieval‑Augmented Generation (RAG) solutions, AI agents, and multi‑agent systems.
• Integrate AI solutions with enterprise platforms, databases, and business applications.
• Work directly with business stakeholders to gather requirements and translate them into production‑ready software.
• Develop modular, reusable components that can be leveraged across multiple AI initiatives.
• Implement GenAIOps practices including CI/CD pipelines, monitoring, evaluation frameworks, and operational governance.
• Ensure solutions meet enterprise standards for scalability, security, reliability, and maintainability.
• Collaborate with architects and technical leaders to evolve reusable AI platform capabilities.

• Strong Object‑Oriented Programming (OOP) principles
• React
• Type Script
• REST API development and enterprise integrations
• Databricks
• Production deployment of Large Language Model (LLM) applications
• Retrieval‑Augmented Generation (RAG)
• Agentic AI solutions
• Prompt engineering and orchestration

• GenAIOps
• Monitoring and observability
• AI evaluation frameworks
• Performance optimization
• Production support

Successful candidates will have experience delivering production AI solutions such as:

• AI‑powered document extraction and classification
• Retrieval‑Augmented Generation (RAG) applications
• Enterprise Q&A chatbots
• Agentic AI solutions
• Multi‑agent AI systems
• Enterprise search platforms
• Policy and knowledge search solutions
• Decision support applications
• Document and data validation solutions
• HR and business process automation
• AI solutions leveraging both structured and unstructured data

Our client is building an AI Centre of Excellence focused on delivering enterprise‑scale AI solutions that transform business operations. They are seeking a Lead Full Stack GenAI Developer who is passionate about building production‑ready Generative AI applications from architecture through deployment.

This is a highly technical, hands‑on engineering role. The successful candidate will take solution designs and build scalable, secure, enterprise‑grade AI applications that solve real business problems. You’ll work closely with architects, business stakeholders, and cross‑functional teams to deliver end‑to‑end AI solutions that can be reused across the organization.

• Design, develop, and deploy enterprise‑grade Generative AI applications using the Microsoft Azure AI ecosystem.
• Build scalable, reusable backend services and APIs using Python and object‑oriented programming principles.
• Develop modern, responsive frontend applications using React and Type Script.
• Design and implement Retrieval‑Augmented Generation (RAG) solutions, AI agents, and multi‑agent systems.
• Integrate AI solutions with enterprise platforms, databases, and business applications.
• Work directly with business stakeholders to gather requirements and translate them into production‑ready software.
• Develop modular, reusable components that can be leveraged across multiple AI initiatives.
• Implement GenAIOps practices including CI/CD pipelines, monitoring, evaluation frameworks, and operational…