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Tier-1 bank brand increases applicant density but senior specialized role limits competition.
High because role requires deep data engineering, ML/LLM, and enterprise AI deployment experience.
High due to explicit 12+ years and extensive mandatory AI, data engineering, and deployment skills.
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Design, develop, and maintain scalable ETL processes and data pipelines using Python and related libraries for large volume data management.
Implement, optimize, and monitor advanced AI and machine learning solutions including integrating large language models (LLMs) and agentic AI systems.
Own robust API design, application development, system design, and operational stability for AI-driven enterprise technology initiatives as an individual contributor.
12+ years of experience in data domain and engineering scalable enterprise AI solutions.
Expert-level proficiency in Python (including frameworks like FastAPI, Flask, PySpark) and/or Java (Spring Boot, Spring Cloud).
Proficiency in database technologies such as Oracle, Postgres, or MongoDB and creating complex SQL/PLSQL scripts.
Deep understanding of AI concepts, including knowledge representation, automated planning, and multi-agent systems, plus hands-on experience with AI/ML frameworks (TensorFlow, PyTorch).
Senior-level technologist with demonstrated expertise in engineering end-to-end AI data pipelines and integrating LLMs within agentic AI systems.
Experienced individual contributor comfortable owning complex system and application design including microservices, API-first design, and event-driven architectures.
Practitioner in agile environments with strong software development best practices including CI/CD, version control, testing, and security applied to AI and data engineering projects.