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.