Back
Strong brand, mid-level (5–8 yrs) Bengaluru role increases applicant density despite specialist requirements.
Highly specialized GenAI and LLM framework expertise reduces cross-industry transferability.
Explicit 5–8 years plus 2–3 years GenAI and specific LLM/agentic framework requirements.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, develop, test, and deploy generative AI and multi-agent AI solutions leveraging large language models and multi-agent frameworks.
Develop and integrate AI agents that operate autonomously or collaboratively, optimizing metrics like task completion rate, response time, and adaptability.
Implement and enhance agentic AI features including autonomous decision-making, collaboration, resource utilization, and explainability within cloud and on-prem environments.
5 to 8 years of experience as a Data Scientist with 2 to 3 years in Generative AI solution development.
Proficiency in generative AI frameworks (LlamaIndex, Langchain, Autogen) and multi-agent frameworks (AutoGen, LangGraph, LangChain, CrewAI).
Hands-on experience with large language models (GPT, LLaMA, Mistral, etc.) and cloud services (Azure, GCP, AWS).
Strong understanding of AI agent collaboration, autonomous decision-making, and integration with vector databases and guardrails.
Experienced data scientist specializing in generative and agentic AI technologies with multi-year hands-on development exposure.
Practical knowledge in deploying multi-agent systems and LLM-powered AI workflows focusing on autonomy, collaboration efficiency, and task success metrics.
Solid background using a wide range of AI/ML tools and frameworks including Python, deep learning architectures, NLP libraries, and reinforcement learning in cloud/on-prem settings.