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.