Gen AI Architect - BSL - Brajesh

About the Role :

We are seeking a highly skilled and forward-thinking Generative AI Architect / Data Scientist to lead the design and implementation of cutting-edge AI systems. You will be responsible for building intelligent, agentic AI applications using large language models (LLMs), LangChain, and other advanced generative AI technologies. This role blends deep technical expertise in AI / ML with hands-on architecture and data science responsibilities.

You'll work across teams to develop AI agents, pipelines, and services that leverage the latest in generative AI, including LLM orchestration, tool use, and autonomous workflows.

Key Responsibilities :

Architect and implement generative AI applications using LLMs and frameworks like LangChain , LlamaIndex , and vector databases (e.g., Pinecone, Weaviate, FAISS).

Build and deploy agentic AI systems that use tools, memory, and multi-step reasoning to solve real-world problems.

Work closely with stakeholders to identify use cases and translate them into AI-powered solutions using Python and modern AI / ML frameworks.

Develop, fine-tune, and evaluate foundation models (e.g., GPT, Claude, Mistral, LLaMA) for domain-specific applications.

Create and maintain scalable, production-grade ML pipelines , from data preprocessing to inference and monitoring.

Leverage LangChain to orchestrate LLMs, tools, APIs, and knowledge sources in agent-based workflows.

Apply prompt engineering , retrieval-augmented generation (RAG) , and fine-tuning techniques for performance improvement.

Collaborate with data engineers, product managers, and ML engineers to ensure AI systems are robust, ethical, and scalable.

Stay updated with the latest research and trends in generative AI, LLMs, and agentic architectures.

Required Qualifications :

Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.

5+ years of experience in AI / ML, with 1 2 years focused on generative AI or LLM-based systems .

Strong programming skills in Python and hands-on experience with AI / ML libraries like PyTorch , Transformers (Hugging Face) , and LangChain .

Deep understanding of agentic AI concepts including planning, tool use, memory management, and autonomous agents.

Experience with vector databases , embedding models , and RAG pipelines .

Ability to build, fine-tune, or integrate with foundation models (e.g., OpenAI, Anthropic, Cohere, Mistral, Meta).

Knowledge of cloud platforms (AWS, GCP, or Azure) and deploying AI solutions in production environments.