Job description
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.
Required Skill Profession
Computer Occupations