Fullstack Developer - Gen AI

Responsibilities:

• Design and develop large-scale, modern front end web applications using Javascript/TypeScript with frameworks like React.js or Angular.
• Build and maintain robust backend services and RESTful APIs using Python frameworks such as FastAPI, Flask, or Django.
• Integrate and deploy Generative AI solutions using large language models (LLMs) to solve real-world business problems.
• Collaborate with cross-functional teams including product managers, UX designers, testers, and other engineers to deliver end-to-end solutions in an Agile environment.
• Ensure code quality, performance, and scalability through best practices in testing, CI/CD, and code management with GitHub.
• Stay current with emerging technologies and contribute to the continuous improvement of development processes.

Key Skills:

• Expert building front end web applications using React.js or Angular with Javascript/Typescript.
• Expert in Python programming with experience in RESTful APIs (FastAPI, Flask, etc) and databases (Azure SQL, CosmosDB, etc.)
• Demonstrated experience building applications that incorporate Generative AI and LLMs (e.g Azure Open AI, Gemini, etc.) Examples include conversational (chat) applications with Retrieval Augmented Generation (RAG) or leveraging agentic frameworks and NLP to process documents.
• Experience with one or more major cloud environment (Azure or GCP)
• Strong expertise using GitHub and developing collaboratively with branching and merging techniques.
• Strong problem-solving skills, attention to detail, and ability to work as part of a team.
• Knowledge of at least one AI framework (LangChain, LangGraph, Autogen, Semantic Kernel, Google ADK, etc.)

Preferred Skills:

• Experience with Azure OpenAI and Azure Document Intelligence or Vertex AI and associated tooling.
• Experience with more than one multi-agent AI framework.
• Experience with advanced NLP tasks like text generation, entity extraction, summarization, and question answering, familiarity with reinforcement learning algorithms and their application in intelligent agent design.
• Understanding of advanced parsing and chunking techniques for optimizing RAG.
• Familiarity with containerization technologies (e.g., Docker, Kubernetes).