Senior AI Engineer

About the Role

IndusInd Banks AI Centre of Excellence is looking for a highly skilled Senior AI Engineer to design, develop, and deploy next-generation AI/ML and Generative AI solutions. The role demands strong hands-on programming expertise, experience in building production-ready AI systems, and the ability to independently deliver scalable enterprise-grade solutions while mentoring junior team members.

Key Responsibilities

• Design, build, and deploy AI/ML models and Generative AI applications using Python on the Databricks platform.
• Develop and implement LLM-powered solutions, including prompt engineering, Retrieval-Augmented Generation (RAG), embeddings-based workflows, and API-driven model inference.
• Write high-quality, production-grade code for data preprocessing, feature engineering, model training, evaluation, and deployment.
• Build and maintain scalable data pipelines using Azure Data Lake Storage (ADLS Gen2), Delta Lake, and Delta Live Tables.
• Operationalize AI solutions through MLflow, model serving, monitoring frameworks, and CI/CD pipelines.
• Develop AI agents, multi-agent systems, guardrails, and traceability mechanisms for enterprise AI use cases.
• Collaborate closely with Data Scientists, Product Managers, Data Engineers, and AIOps teams to deliver impactful business solutions.
• Conduct code reviews, provide technical guidance, and mentor junior AI Engineers to support capability development within the team.

Required Qualifications & Skills

• 2 to 5 years of hands-on experience in AI/ML Engineering, Software Development, Data Science, or Generative AI solution development.
• Strong proficiency in Python and AI/ML libraries, including NumPy, Pandas, Scikit-learn, PyTorch, and TensorFlow.
• Solid understanding of Machine Learning concepts, including supervised and unsupervised learning, feature engineering, model evaluation, and deployment.
• Practical experience with Large Language Models (LLMs), prompt engineering, embeddings, vector search, RAG architectures, and API-based model integration.
• Hands-on experience with Databricks, including notebooks, workflows, MLflow, model serving, and deployment practices.
• Experience working with Azure cloud services, particularly ADLS Gen2 and related data engineering components.

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• Strong knowledge of SQL, REST APIs, Git, and software engineering best practices.
• Understanding of MLOps and LLMOps concepts, including model registry, monitoring, staged deployments, retraining workflows, and governance.
• Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related discipline.

Preferred Qualifications

• Experience with Agentic AI frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, or Databricks Agent Framework.
• Prior experience in the Banking, Financial Services, or FinTech domain.
• Familiarity with Responsible AI practices, model governance, guardrails, explainability, monitoring, and auditability requirements.
• Exposure to enterprise-scale AI deployments and cloud-native architectures.