AI Lead Engineer

Role Summary: We are seeking a highly experienced AI Lead Engineer to lead the design, development, and deployment of enterprise-scale Artificial Intelligence and Generative AI solutions. The ideal candidate will be responsible for driving AI strategy, defining technical architecture, mentoring engineering teams, and delivering scalable AI-powered applications that create measurable business value. Key Responsibilities: AI Solution Architecture & Leadership: - Lead the design and implementation of AI/ML and Generative AI solutions across enterprise platforms. - Define AI architecture, engineering standards, and best practices. - Provide technical leadership and mentorship to AI engineers, data scientists, and software developers. - Evaluate emerging AI technologies and recommend solutions aligned with business objectives. - Drive innovation and AI adoption across the organization. Generative AI & LLM Development: - Design and build applications using Large Language Models (LLMs). - Develop enterprise solutions leveraging Azure OpenAI, OpenAI, Claude, Gemini, or similar platforms. - Architect and implement Retrieval-Augmented Generation (RAG) solutions. - Develop AI agents, copilots, intelligent assistants, and document processing solutions. - Lead prompt engineering, model evaluation, fine-tuning, and optimization initiatives. AI Engineering & MLOps: - Build scalable AI services, APIs, and microservices. - Implement model deployment, monitoring, observability, and MLOps pipelines. - Develop data pipelines to support training and inference workloads. - Optimize model performance, scalability, reliability, and cost efficiency. - Ensure AI solutions meet security, governance, and compliance requirements. Cloud & Platform Engineering: - Deploy and manage AI solutions on Azure, AWS, or GCP. - Work with vector databases, embeddings, semantic search, and knowledge management platforms. - Leverage containerization and orchestration technologies such as Docker and Kubernetes. - Collaborate with enterprise architecture teams to integrate AI solutions into existing systems. Stakeholder & Delivery Management: - Partner with business leaders and product teams to identify and prioritize AI use cases. - Translate business requirements into technical AI solutions. - Lead Agile delivery teams and manage project risks, dependencies, and milestones. - Present architecture, solution designs, and implementation strategies to stakeholders. Required Skills: - Strong experience in Python and AI/ML solution development. - Expertise in Generative AI, Large Language Models (LLMs), Machine Learning, Deep Learning, and NLP. - Hands-on experience with Azure OpenAI, OpenAI APIs, LangChain, LlamaIndex, Hugging Face, Semantic Kernel, or similar frameworks. - Strong experience in RAG, Fine-Tuning, Prompt Engineering, AI Agents, and Vector Databases. - Knowledge of TensorFlow, PyTorch, Scikit-learn, and related AI frameworks. - Experience in REST APIs, Microservices, Docker, Kubernetes, and CI/CD pipelines. - Strong cloud experience with Azure, AWS, or GCP. - Excellent leadership, communication, stakeholder management, and problem-solving skills. Preferred Skills: - Experience leading enterprise AI transformation programs. - Knowledge of Responsible AI, AI Governance, Security, and Compliance frameworks. - Experience with MLOps platforms and model lifecycle management. - Exposure to healthcare, banking, insurance, or other regulated industries. - AI, Cloud, or Architecture certifications are preferred. Key Competencies: - AI Strategy & Solution Architecture - Technical Leadership & Mentoring - Generative AI & LLM Expertise - AI Agent & RAG Development - Machine Learning & MLOps - Cloud Architecture - Stakeholder Management - Innovation & Problem Solving - Agile Delivery - Ownership & Accountability.