What You'll Be Doing: 

• Support build end-to-end GenAI applications such as chatbots, voicebots, Talk-to-Data systems, where you will help buiild: data ingestion, retrieval layer, orchestration (e.g. LangChain/LlamaIndex/LangGraph), API/backend, and simple UI where needed.
• Implement RAG pipelines with vector databases, hybrid search, rerankers, query transformation, and evaluation frameworks for relevance and robustness.
• Perform model selection, prompting strategies, and finetuning (LoRA/QLoRA/SFT) for text, code, and multimodal models, including guardrails, output evaluation and A/B testing.
• Integrating and optimizing LLMs interaction with external tools, APIs, and data sources in a standardized and scalable way by using Model Context Protocol (MCP) connectors
• Business understanding and translating problems into technical goals by defining tasks, auditing data feasibility, and highlighting issues.
• Supporting project delivery

What We’re Looking For:  

• Familiarity with theory behind various deep learning concepts
• Experience with Machine Learning (ML), especially in Generative AI (LLM/LMM) with focus on Natural Language Processing (NLP) or multimodal models.
• Fluency in Python and object programing, working knowledge of SQL and vector database 
• Tech stack in Azure or GCP cloud
• Knowledge of specific Deep Learning and GenAI libraries like: NumPy, PyTorch, HuggingFace, LangChain, LangGraph and GenAI APIs i.e. OpenAI/Gemini.
• Experience with microservice architectures
• Experience with code repositories and code assistants
• Strong business acumen
• Ability to come up with creative solutions to address customer problem

 Nice to have:

• Experience in working with Databricks will be a plus
• Commercial experience proven by multiple successful projects in Generative AI, Natural Language Processing or Computer Vision will be a big plus