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Strong multinational brand and Bangalore location increase applicant density despite niche agentic AI specialization.
Deep agentic LLM, RAG, and MLOps expertise limits cross-industry transferability.
Mandatory six-plus years, specific agentic LLM experience, and demonstrable projects make filters strict.
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Lead design, architecture, and delivery of multi-agent AI systems integrating LLMs, tools, APIs, and human-in-the-loop controls to automate high-value business processes.
Build, productionize, and maintain robust data science and machine learning solutions with focus on retrieval-augmented generation (RAG), knowledge-grounding, evaluation, safety, and continuous improvement.
Provide technical leadership including mentoring, defining architecture, establishing evaluation frameworks, and engaging senior stakeholders for measurable business impact.
Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, Data Science, Engineering or related quantitative field.
Minimum 6 years of professional experience in data science, ML, applied AI, or software engineering, with at least 2 years working on LLM, generative AI, or agentic AI solutions.
Demonstrable hands-on experience building and delivering complex connected agentic systems (beyond simple chatbots) with evidence of individual contribution.
Strong proficiency in Python programming, SQL, data engineering, machine learning fundamentals, and production software engineering practices including version control and CI/CD.
Experienced in architecting and deploying multi-agent AI workflows combining LLMs, APIs, retrieval systems, and human controls in production or pilot environments.
Skilled at translating ambiguous business problems into reliable, scalable AI solutions with focus on safety, evaluation, monitoring, and responsible AI practices.
Capable technical leader and communicator, able to mentor teams, influence stakeholders, and balance rapid experimentation with production reliability.