Seeking a skilled GenAI Architect to spearhead the design, development, and scaling of enterprise-grade Generative AI solutions. This role requires profound expertise in Azure AI services, RAG architectures, and AI governance. You will collaborate closely with backend and frontend teams to deliver robust, production-ready applications.

This position offers an exciting opportunity to work with cutting-edge AI technologies and shape the future of AI-driven applications within an enterprise environment. You will be instrumental in driving innovation and ensuring responsible AI practices.

Architect and implement comprehensive GenAI solutions utilizing the Azure ecosystem, including Azure OpenAI and Cognitive Search. Develop and enforce critical AI guardrails to ensure safety, compliance, and responsible AI usage. Construct scalable, secure, and high-performance AI systems that adhere to enterprise standards. Implement conversational AI applications using NodeJS, Azure OpenAI, and Python. Integrate diverse AI technologies such as OpenAI models, LangChain, and Azure Cognitive Services to enable advanced natural language capabilities. Establish private endpoints across Azure services to enhance application security and performance. Develop and deploy production applications on Azure, meeting stringent security, reliability, and compliance requirements. Build tools for data annotation, model performance monitoring, and continuous application improvement. Mentor junior developers and provide training on best practices for conversational AI development.

Possess 10-12 years of extensive technology experience in core application development. Bring over 5 years of dedicated experience leading the development of AI applications and conversational interfaces. Demonstrate hands-on, implementation-focused knowledge of generative AI tools on the Azure cloud. Exhibit deep, hands-on development proficiency in Python and NodeJS. Leverage hands-on expertise with SharePoint indexes and data/file structures (Azure SQL). Utilize hands-on knowledge of Azure Form Recognizer tools. Experience with LangChain, Azure OpenAI, and Azure Cognitive Search is essential. Apply expertise in Retrieval Augmented Generation (RAG) and RLHF using Python. Develop solutions with vector databases on Azure cloud using PostgreSQL. Familiarity with prompt engineering via LangChain or Llama Index. Showcase knowledge of NLP techniques like transformer networks, embeddings, and intent recognition. Demonstrate hands-on skills in embedding and fine-tuning Azure OpenAI using MLOPS/LLMOPS pipelines. Strong communication, DevOps, and collaboration skills are highly desirable.