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Metro Bengaluru and known brand raise competition, offset by seniority and niche GenAI/lakehouse specialization.
Medium because core data and GenAI skills transfer across industries but require enterprise AI architecture experience.
High because explicit senior experience (8+ years), mandatory AI/ML architecture experience and specialized GenAI skillset.
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Design and implement GenAI workflows, including prompt engineering and integration into enterprise applications using Python.
Architect and manage multi-LLM gateways for dynamic model selection, benchmarking, and enterprise-grade performance.
Develop agentic workflows for autonomous task orchestration and maintain data lakehouse environments with knowledge management and semantic search capabilities.
Bachelor’s or Master’s degree in Computer Science, Data Sciences, or related fields.
8–12+ years in technology roles, including at least 3–5 years in AI/ML solution architecture or enterprise AI implementation.
Proficiency in Python programming and experience with GenAI/LLM systems.
Work Experience Required: 8–12+ years with 3–5 years specifically in AI/ML solution architecture or enterprise AI implementation.
Experienced in architecting complex AI/ML systems with a focus on enterprise integration and operational efficiency.
Skilled in managing multi-LLM strategies balancing accuracy and cost in production environments.
Capable of leading AI governance, knowledge distillation, and observability frameworks for scalable GenAI applications.