About the job Gen AI / 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
- Closed source LLMs such as OpenAI 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
- Good knowledge of advanced statistical methods. Experience working with Text Data using transformer-based model
- Expertise with the following scripting languages:
- Knowledge Graphs
- Good and experience of machine learning algorithms and ability to apply them in supervised and
- 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
- modeling and so on
- Experience building and fine-tuning Language Models (LMs), such as BERT, ELMo, XLNet etc to solve bespoke NLP tasks
- Tech-savvy 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
- 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
- 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
- Strong grasp of deep learning architectures, including CNNs, RNNs, Transformers, GANs, and
- 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