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Specialized senior GenAI role reduces pool, but Chennai metro increases applicant density.
Core GenAI and ML engineering skills are transferable, though enterprise energy domain adds moderate specificity.
Explicit 8+ years and mandated LLM, RAG, vector DB, and MLOps requirements enforce strict filters.
Design, build, and scale generative AI (GenAI) and agentic systems capable of reasoning, planning, and executing complex tasks.
Lead end-to-end delivery of GenAI initiatives including defining reusable design patterns, frameworks, and ensuring responsible AI adoption balancing performance, cost, reliability, and governance.
Collaborate closely with product owners, ML engineers, application developers, and business SMEs to integrate GenAI capabilities into enterprise applications with human-in-the-loop and professional decision-making.
Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or similar.
8+ years of experience in AI/ML, software engineering, data or analytics focusing on digital solutions development.
5-8 years of core AI/ML solution development experience with specialization in NLP and applied GenAI systems.
Practical experience with LLM ecosystems (e.g., OpenAI, Azure OpenAI), prompt engineering, RAG architectures, vector databases, API/microservices integration, and containerized environments.
Strong expertise in architecting scalable, reliable GenAI systems emphasizing performance, cost, latency, and user experience.
Demonstrated experience designing agentic workflows including planning, tool usage, memory management and multi-step reasoning pipelines.
Effective collaborator with experience in global distributed teams, able to mentor and align cross-functional groups including AI/ML engineering, platform, and MLOps teams.