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Tier-1 brand, metro location, and visible senior Data/AI title attract many qualified applicants.
Technical data engineering and AI skills transfer across industries, but leadership and agentic AI experience add domain specificity.
Explicit 12+ years requirement plus numerous mandatory AI, data, and platform skills increases filter rigidity.
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Design, develop, and maintain scalable ETL processes and data pipelines using Python and SQL to manage large volume data.
Implement AI engineering solutions including AI frameworks, model context protocols (MCPs), and APIs for agentic AI systems with large language model integration.
Ensure operational stability and performance of AI initiatives through system design, application development, and adherence to software development best practices including CI/CD and security.
12+ years of experience in the data domain with expertise in handling large volume data.
Expert-level proficiency in Python (including FastAPI, Flask, PySpark) or Java (Spring Boot ecosystem).
Proficiency in database technologies such as Oracle, Postgres, or MongoDB and strong SQL/PLSQL skills.
Experience with AI engineering methodologies, frameworks (TensorFlow, PyTorch), and relevant AI technologies including LLMs and agentic AI systems integration.
Senior-level individual contributor skilled in designing and executing scalable, enterprise-grade AI and data engineering solutions.
Experienced in full-stack development with proficiency in Python, UI frameworks (Angular, React), and microservice architectures.
Strong expertise in AI system design, model deployment, and implementation of AI services APIs with a focus on operational stability and modern development practices.