Tech Lead - AI

Job description

Job Summary We are seeking a skilled lead AI Engineer to join our AI initiatives team in the IT Department. The role involves designing, developing, and deploying AI/ML solutions with a focus on Generative AI, Retrieval-Augmented Generation (RAG), and Agentic AI frameworks. The candidate will collaborate with cross-functional teams to build scalable and compliant AI solutions that enhance banking operations and customer experience. Key Responsibilities • Design and implement AI/ML models leveraging LLMs, SLMs, RAG pipelines, and Agentic AI frameworks. • Develop end-to-end AI workflows, including data ingestion, preprocessing, model training, fine-tuning, and deployment. • Collaborate with data engineers to integrate structured and unstructured banking data securely. • Implement and optimize vector databases, embeddings, and retrieval mechanisms. • Ensure AI model governance, explainability, and compliance with banking regulations. • Work with business and domain experts to translate requirements into AI-driven solutions. • Monitor model performance, implement feedback loops, and continuously improve AI systems. • Stay updated on emerging AI technologies and frameworks relevant to banking use cases. Required Skills & Qualifications • Relevant work experience of 8+ years with Generative AI, LLMs/SLMs, RAG architecture, and vector databases (e.g., Pinecone, FAISS, Weaviate). • Bachelor's/master's degree in computer science, Data Science, AI/ML, or related fields. • Strong programming skills in Python (TensorFlow, PyTorch, LangChain, Hugging Face, etc.). • Hands-on knowledge of Agentic AI frameworks (e.g., LangGraph, AutoGen, CrewAI, or similar). • Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices (Docker, Kubernetes, CI/CD). • Understanding of data security, compliance, and governance frameworks in regulated industries (preferably banking/finance). • Mentoring team on problem-solvings, analytical mindset and guiding them to work in Agile. Preferred Qualifications • AI/ML certifications (e.g., AWS AI/ML Specialty, Microsoft AI Engineer, NVIDIA Deep Learning, Generative AI certifications). • Experience with prompt engineering, fine-tuning, and RAG-enhanced GenAI models. • Exposure to agent-based AI solutions in enterprise settings. • Knowledge of banking/financial domain processes (risk, compliance, KYC, lending, fraud detection).