Agentic AI Architect (Data Scientist – Generative AI & Deep Learning)

Position : Agentic AI Architect (Data Scientist – Generative AI & Deep Learning)

Experience : 4–7 Years

Location : Pune (Hybrid – Viman Nagar) / Remote

Notice Period : Immediate to 10 Days

Role Overview

We are looking for a highly skilled Agentic AI Architect with deep expertise in Generative AI, Deep Learning, and NLP , along with hands-on experience deploying ISG Agentic frameworks . The ideal candidate combines strong technical depth with client-facing consulting experience. This role involves designing, architecting, and deploying Agentic AI systems, LLM-driven solutions, and autonomous reasoning workflows to address complex business problems and drive innovation.

Key Responsibilities

Partner with clients to understand business objectives and translate them into scalable AI / ML solutions.

Architect and deploy ISG Agentic systems enabling intelligent, autonomous, and multi-agent workflows.

Design and implement Retrieval-Augmented Generation (RAG) pipelines for contextual knowledge retrieval and response enhancement.

Utilize frameworks such as LangGraph, LangChain, AutoGen , or custom multi-agent systems to enable decision automation and reasoning.

Apply prompt engineering techniques to refine LLM performance and ensure response precision.

Develop and fine-tune Deep Learning and NLP models for use cases including summarization, entity extraction, Q&A, and conversational AI.

Integrate Generative and Agentic AI solutions seamlessly into enterprise ecosystems.

Create transparent, structured reasoning workflows (chain-of-thought logic) to support explainability and auditability.

Collaborate with cross-functional teams to ensure scalability, performance, and readiness for production deployment.

Stay current with advancements in LLMs, Agentic AI, multimodal learning, and autonomous AI research.

Required Skills & Qualifications

4–7 years of hands-on experience in AI / ML, NLP, Deep Learning, and Generative AI projects.

Proven client-facing experience with strong communication and presentation skills.

Mandatory : Practical deployment experience with ISG Agentic frameworks or agentic AI architectures.

Proficiency in RAG design and implementation using frameworks such as LangChain, LangGraph, LlamaIndex, or similar.

Strong programming expertise in Python , with deep familiarity with ML / AI libraries : PyTorch, TensorFlow, Hugging Face, Transformers.

Solid understanding of Deep Learning techniques (CNNs, RNNs, Transformers, Attention Mechanisms, etc.) and model optimization.

Experience with vector databases (e.g., Pinecone, FAISS, Weaviate, Chroma) for knowledge indexing and retrieval.

Exposure to cloud platforms (AWS, Azure, GCP) and scalable deployment pipelines (Docker, Kubernetes, CI / CD).

Strong analytical mindset and structured problem-solving with clear documentation and reasoning.

Good to Have

Experience building end-to-end Agentic AI or Generative AI products from POC to production.

Exposure to fine-tuning and optimizing LLMs for domain-specific applications.

Familiarity with multimodal AI, reinforcement learning , or autonomous decision-making systems.

Understanding of data governance, model interpretability , and Responsible AI principles.