Technical Lead-App Development

Role overview

Responsibilities

• Implement a conversational AI application using NodeJS, Azure OpenAI, and Python.
• Integrate OpenAI models, LangChain, and Azure Cognitive Services, including Cognitive Search, indexes, indexers, and APIs.
• Implement private endpoints and build schemas, APIs, frameworks, and platforms to operationalize models.
• Develop conversation workflows, context handling, personalized recommendations, and sentiment analysis.
• Deploy the production application on Azure, meeting security, reliability, and compliance standards.
• Build tools for training-data annotation and model-performance monitoring, and continuously improve the application.
• Mentor developers and train them in conversational AI development practices.
• Build and productionize Azure cloud vector databases.

Experience and technical requirements

• 6–8 years of overall technology experience in core application development and 2+ years leading AI application and conversational-interface development.
• Hands-on generative AI implementation experience on Azure; strong Python and NodeJS development proficiency.
• Hands-on experience with SharePoint indexes and data/file structures, Azure SQL, and Azure Form Recognizer.
• Experience with LangChain, Azure OpenAI, and Azure Cognitive Search.
• Experience with RAG and RLHF using Python; Azure vector databases using PostgreSQL.
• Prompt engineering with LangChain or LlamaIndex; knowledge of NLP, transformers, embeddings, and intent recognition.
• Hands-on Azure OpenAI embedding and fine-tuning using MLOps/LLMOps pipelines.

Additional technologies

• Pinecone, FAISS, Weaviate, or ChromaDB experience is listed as an alternative vector database qualification.
• Strong communication, DevOps, and collaboration skills are described as good to have.