Technical Lead-AI ML

We are seeking a highly skilled and experienced Technical Lead AI/ML Generative AI to lead the design, development, deployment, and scaling of enterprise-grade AI solutions. The ideal candidate will have strong expertise in Machine Learning, Deep Learning, Generative AI, Agentic AI, MLOps, Data Engineering, and Cloud-Native AI Platforms. The candidate will be responsible for leading AI initiatives, mentoring engineering teams, driving AI innovation, and delivering scalable AI products across business domains such as Financial Services, Lending, Customer Experience, Risk Analytics, Document Intelligence, and Intelligent Automation. Key Responsibilities AI Solution Architecture Design Design scalable AI/ML architecture for enterprise applications. Lead AI platform strategy and technology roadmap. Define end-to-end AI solution architecture including Data Ingestion Feature Engineering Model Training Model Deployment Model Monitoring Design AI-driven products using cloud-native architecture principles. Create reusable AI frameworks and accelerators. Generative AI Agentic AI Lead implementation of Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Multi-Agent Systems Agentic AI Platforms Prompt Engineering Frameworks AI Workflow Automation Machine Learning Deep Learning Design and develop Classification Models Regression Models Recommendation Engines Forecasting Models Anomaly Detection Systems Computer Vision Solutions NLP Applications Hands-on expertise in Scikit-Learn TensorFlow PyTorch XGBoost LightGBM Hugging Face RAG Knowledge Systems Architect enterprise-grade RAG solutions Vector Databases Semantic Search Hybrid Search Knowledge Graphs Embedding Pipelines Experience with LangChain LangGraph LlamaIndex Haystack Vector Databases Pinecone ChromaDB Weaviate Milvus FAISS MLOps AI Platform Engineering Lead AI platform deployment and governance Model Lifecycle Management Model Registry Model Monitoring Drift Detection Feature Stores Tools MLflow Kubeflow Airflow SageMaker Vertex AI Databricks Implement CI/CD for AI Models Automated Training Pipelines Continuous Model Deployment Cloud Infrastructure Architect AI workloads on AWS Azure OCI GCP Services AWS Bedrock SageMaker EC2 EKS Lambda S3 Containerization Docker Kubernetes Deployment Models On-Premise Hybrid Cloud Multi-Cloud AI Governance, Security Compliance Establish AI governance framework Responsible AI Explainable AI (XAI) Model Auditing AI Risk Management Leadership Team Management Lead AI/ML engineering team. Mentor Data Scientists and AI Engineers. Conduct architecture reviews and code reviews. Drive best practices in AI engineering. Collaborate with Product Owners and Business Teams. Own end-to-end AI solution delivery.