Tech Lead Generative AI Solutions

iFlow is hiring Tech Lead Generative AI Solutions Tech Lead Generative AI Solutions Role Overview We are looking for a highly skilled Tech Lead Generative AI Solutions to drive end to end development of AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Azure AI services. The role focuses on hands on engineering, team guidance, and ensuring high quality AI outputs. Knowledge of Copilot extensibility and test frameworks such as RAGAS is highly desirable. Key Responsibilities 1. Hands-on Development: Build and enhance Generative AI solutions using Azure OpenAI and other Azure AI tools. Develop RAG pipelines chunking, embeddings, vector indexing, retrieval logic. Implement LLM-based applications using LangChain, Semantic Kernel, etc. Build extensions/plugins for Copilot (Copilot Studio, Graph Connectors). Create APIs and services supporting AI workflows. 2. Technical Leadership: Mentor engineering teams and guide implementation best practices. Conduct code reviews ensuring quality and security. Collaborate with product teams to align technical outputs with requirements. 3. Evaluation Quality Assurance: Use evaluation frameworks like RAGAS or DeepEval. Establish processes for testing LLM outputs (accuracy, hallucinations, safety). Support CI/CD and monitoring of AI components. 4. Collaboration Documentation: Work with platform, data, and ML teams for integration. Develop documentation and reusable AI components. Required Qualifications Technical Skills: Hands-on experience with Azure OpenAI, Cognitive Search, Azure ML, and related services. Strong skills in LLMs, RAG pipelines, embeddings, vector databases, and prompt engineering. Programming experience in Python , Fast API, React / TypeScript Should Have good experience on handling unstructured structured data including working with non-relational models relational models. Should have experience in SQL, MySQL, Cosmos DB Familiarity with LangChain, Semantic Kernel, and vector DBs such as Pinecone or Redis Vector. Knowledge of Copilot extensibility (plugins, connectors). Experience using RAGAS or similar AI evaluation tools. Soft Skills: Leadership and mentoring abilities. Strong debugging and analytical skills. Excellent communication skills. Good-to-Have Skills Exposure to MLOps on Azure ML. Understanding of ETL/data preparation for RAG. Experience with multimodal AI (Vision, Document Intelligence, Speech). Familiarity with Responsible AI principles. Education Experience Bachelor s or Master s degree in Computer Science, Engineering, or related field. 7 12 years of software engineering experience with 2 3 years in AI/LLM projects. Prior technical leadership experience preferred. Disclaimer :This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.