Role & responsibilities
Design, fine-tune, and deploy Generative AI/LLM models for use cases such as knowledge assistants, document intelligence, automation, and decision support.
Collaborate with business stakeholders to understand domain problems and develop AI-powered solutions.
Implement RAG (Retrieval-Augmented Generation), agentic workflows, and vector database integrations for domain-specific applications.
Research, experiment, and apply latest advancements in transformers, diffusion models, and multi-modal AI (text, image, and voice).
Build prototypes, PoCs, and scalable solutions for business functions such as project management, engineering design, supply chain optimization, and customer interactions.
Stay updated with latest GenAI research.
Ensure ethical AI practices, data security, and compliance in all deployments.
Preferred candidate profile
Strong programming in Python (preferred), with experience in LangChain, PyTorch, TensorFlow, Hugging Face or similar frameworks. Hands-on with LLMs such as OpenAI GPT-3.5/4, Google Gemini, Meta LLaMA, AWS Bedrock, or open-source models (Mistral, Falcon, etc.).
Knowledge of RAG, agentic AI workflows, prompt engineering, vector databases (Pinecone, Weaviate, PG Vector, FAISS), and graph databases (Neo4J).
Familiar with GANs, diffusion models, and transformer architectures.
Cloud exposure (AWS, Azure, GCP) and containerization tools (Docker, Git).
Working knowledge of SQL and NoSQL databases.
Qualifications
- Bachelor of Technology (B.Tech), Bachelor of Engineering (B.E.), or a Bachelor's/Master's degree in Computer Science, Information Technology, or a related field.
- 3-5 years of professional experience, including 2+ years in Generative AI field
- Prior experience in EPC, Engineering, or Construction domain is a strong plus