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Tier-1 brand, popular AI title, Pune metro, and broad skill requirements increase applicant competition.
Core ML, LLM, and MLOps skills are transferable across industries, though fintech governance introduces moderate domain bias.
Production ML/LLM deployment, cloud and MLOps requirements create moderately strict technical screening criteria.
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Design, develop, and implement AI and Generative AI solutions leveraging LLMs, Agentic AI frameworks, and cloud AI platforms.
Develop and maintain scalable AI/ML pipelines and cloud-native integrations using platforms like Azure, Databricks, and AWS.
Implement Responsible AI and governance practices including bias detection, hallucination mitigation, explainability, and compliance with data ethics.
Bachelor’s degree in Computer Science, Data Science, AI/ML, or related technical field.
Hands-on experience in developing and deploying production-level AI applications.
Experience with Python, Spark or SQL and exposure to at least one cloud platform such as Azure, AWS, or Databricks.
Understanding of AI/ML workflows, APIs, data pipelines, ETL processes, and containerization technologies like Docker or Kubernetes.
Experienced in integrating AI capabilities with APIs, databases, and cloud services for production deployment.
Familiar with AI governance, MLOps and LLMOps best practices, and emerging Generative AI technologies.
Comfortable working in a fast-evolving AI engineering environment with strong analytical and problem-solving skills.