About this role
Job title: GenAI/Agentic AI Specialist
Education and Work Experience Requirements 5 to 9 years of experience as GenAI or Agentic AI specialist 2 to 3 years of experience in Generative AI/ Agentic AI solution development Proven track record and experience with below technologies Open source LLMs like Llama, Gemma, Mixtral etc Closed source LLMs such as Open AI GPT, Azure Open AI, Claude, Gemini etc Prompt Engineering/Tuning, RAG, RAFT, LLM finetuning such as PEFT LoRA QLoRA Understanding of SLMs such as Phi3, BERT and Transformer architecture Vector databases like Pincone, Qdrant etc Good knowledge of advanced statistical methods. Experience working with Text Data using transformer-based model Expertise with the following scripting languages: Python, R, Tensorflow, Keras, Pytorch OpenNLP, CoreNLP, WordNet, NLTK, SpaCy, Gensim, Large Language Models, Knowledge Graphs Good and experience of machine learning algorithms and ability to apply them in supervised and unsupervised NLP tasks Strong understanding of AI agent collaboration, negotiation, and autonomous decision-making Experience in developing and deploying AI agents that operate independently or collaboratively in complex environments Knowledge of NLP algorithms that can handle various NLP tasks such as intent recognition, entity extraction, language modeling, text classification, question answering, text summarization, topic modeling and so on Experience building and fine-tuning Language Models such as BERT, ELMo, XLNet etc to solve bespoke NLP tasks Tech savy and willing to work with open-Source Tools Should have independently handled a project technically and provided directions to the other Team Members Able to lead the project independently Experience in turning ideas into actionable designs Able to persuade stakeholders and champion effective techniques through development Strong interpersonal and communication skills: ability to tell a clear, concise, actionable story with data, to folks across various levels of the company Good to have foundational knowledge on Cloud, API frameworks like Flask, Fast API, Swagger/Postman tools
Mandatory Skills Design, develop, test, and deploy Machine Learning models using state-of-the-art algorithms with a strong focus on language models Strong understanding of LLMs, and associated technologies like RAG, Agents, VectorDB and Guardrails Hand-on experience in GenAI frameworks like LlamaIndex, Langchain, Autogen, etc Deep knowledge of agentic AI principles, including self-improving, self-organizing, and goal-driven agents Proficiency in multi-agent frameworks such as AutoGen, LangGraph, LangChain, and CrewAI for orchestrating AI workflows Hands-on experience integrating LLMs GPT, LLaMA, Mistral, etc with agentic frameworks to enhance automation and reasoning NLP tools and libraries: OpenNLP, CoreNLP, WordNet, NLTK, SpaCy, Gensim Experience in cloud services Interact with our research team and with key partners in the market to build end-to-end AI/ML/NLP solutions: Conversational AI, document understanding and QnA Mine and analyze data, applying statistical methods as necessary, pertaining to customers discovery, and viewing experiences to identify critical product insights Proactively develop new metrics and studies to quantify the value of different aspects of product Drive efforts to enable product and engineering leaders to share your knowledge and insights through clear and concise communication, education, and data visualization Translate analytic insights into concrete, actionable recommendations for business or product improvement Build and improve reusable tools & modelling pipelines and support knowledge sharing across several teams Define and deploy best practices in Machine Learning MLOps/LLMOps, mentor and teach colleagues Deep understanding of Human-Machine Interaction HMI frameworks within cloud and on-prem environments Strong grasp of deep learning architectures, including CNNs, RNNs, Transformers, GANs, and VAEs Partner closely with product and engineering leaders throughout the lifecycle of project
Additional Information A Masters or PhD is preferred Computer Science / Machine Learning/ Mechanical, etc from tier 1 institutions. If Bachelors, Machine Learning or Computer Science specialization only