Senior LLM Engineer GenAI / ML (Python, Langchain)

Job Description

If you are interested fill this form: https://developers.turing.com/invite/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJqb2JJZCI6MzMyNDcsInVzZXJJZCI6MTE3OCwidXNlclJvbGUiOiJUQV9TT1VSQ0VEIiwiaWF0IjoxNzQ0NzM3ODUwfQ.WndOiWb7zy8UiszDNKT9xFHjw4SHqCKEGClcvkXh83s Senior LLM Engineer GenAI / ML (Python, Langchain) Full Time Location: India Overall Experience: 7- 12 Years Focus: Hands-on engineering role focused on designing, building, and deploying Generative AI and LLM-based solutions. The role requires deep technical proficiency in Python and modern LLM frameworks with the ability to contribute to roadmap development and cross-functional collaboration. Key Responsibilities: Design and develop GenAI/LLM-based systems using tools such as Langchain and Retrieval-Augmented Generation (RAG) pipelines. Implement prompt engineering techniques and agent-based frameworks to deliver intelligent, context-aware solutions. Collaborate with the engineering team to shape and drive the technical roadmap for LLM initiatives. Translate business needs into scalable, production-ready AI solutions. Work closely with business SMEs and data teams to ensure alignment of AI models with real-world use cases. Contribute to architecture discussions, code reviews, and performance optimization. Skills Required: Proficient in Python, Langchain, and SQL. Understanding of LLM internals, including prompt tuning, embeddings, vector databases, and agent workflows. Background in machine learning or software engineering with a focus on system-level thinking. Experience working with cloud platforms like AWS, Azure, or GCP. Ability to work independently while collaborating effectively across teams. Excellent communication and stakeholder management skills. Preferred Qualifications: 1+ years of hands-on experience in LLMs and Generative AI techniques. Experience contributing to ML/AI product pipelines or end-to-end deployments. Familiarity with MLOps and scalable deployment patterns for AI models. Prior exposure to client-facing projects or cross-functional AI teams.