Prompt Engineer

Job Description

Greetings from BMW Techworks India Role: Prompt Engineer Location: Bangalore or Chennai Experience: 5 to 8 Years What awaits you/ Job Profile: Develop, deploy, and maintain a Retrieval Augmented Generation (RAG) model for generative AI applications. Design and implement a RAG model that can generate natural language responses, commands, and actions based on user queries and context. Optimize the RAG model for performance, scalability, and reliability, using best practices and robust engineering methodologies. Design, test, and optimize prompts to improve performance, accuracy, and alignment of large language models across diverse use cases. Develop and maintain reusable prompt templates, chains, and libraries to support scalable and consistent GenAI applications. What should you bring along: Collaborative approach towards colleagues Flexibility to learn and adopt quickly (agile) Ownership of deliverables and associated quality Must have technical skill: 5-8 years of progressive experience as a software engineer, preferably within a high growth product tech environment Minimum 2 years experience working with generative AI tools, models, and frameworks, such as Anthropic, OpenAI, Hugging Face, TensorFlow, PyTorch, or Jupyter. Experience in working with RAG models or similar architectures, such as RAG, Ragna, or Pinecone Experience in creating GENAI agents for tools, query planning, automation Experience in designing and optimizing prompts for various LLM use cases (e.g., summarization, classification, translation, conversational and agent workflows). Deep understanding of prompt engineering techniques (zero-shot, few-shot, chain-of-thought, etc.) and their effect on model behaviour. Familiarity with prompt tuning, parameter-efficient fine-tuning (PEFT), and prompt chaining methods. Strong written communication skills with precise and clear writing abilities. Expertise in Agile software product delivery and SCRUM Strong delivery mind-set with the ability to work across multiple teams. Good to have technical skills: Good hands-on experience utilizing AWS (Amazon Web Services) like S3, Lambda, EC2, EKS, API Gateway, ALB/ NLB, IAM Good knowledge of Generative AI, RAG, similarity search and vector databases Good knowledge in MCP and agent to agent protocol.