Retrieval Augmented Generation Engineer

About the Role

The Retrieval Augmented Generation (RAG) Engineer will design, build, and optimize systems that combine information retrieval with large language models to deliver accurate, context-aware responses. This is a full-time, on-site role based in Delhi, India.

Key Responsibilities

• Work closely with product, data, and engineering teams.
• Identify relevant data sources.
• Develop retrieval pipelines.
• Integrate retrieval pipelines with generative AI models.
• Architect RAG workflows.
• Implement vector databases and search indices.
• Fine-tune and evaluate models.
• Improve system performance through experimentation and metrics-driven iteration.
• Ensure data quality.
• Maintain robust production deployments.
• Document solutions.
• Collaborate with stakeholders to translate business requirements into scalable technical designs.

Requirements & Tech Stack

• Strong proficiency in programming for AI/ML systems, ideally with experience in Python and modern software engineering practices (e.g., version control, testing, CI/CD).
• Knowledge of information retrieval, search systems, and vector databases (e.g., Elasticsearch, OpenSearch, Pinecone, Weaviate, FAISS, or similar technologies).
• Hands-on experience with large language models and RAG architectures, including prompt engineering, model integration, and evaluation of generative outputs.
• Understanding of data pipelines and preprocessing, including text cleaning, embedding generation, and structuring unstructured data for retrieval.
• Experience with cloud platforms and deployment frameworks (such as AWS, GCP, Azure, Docker, Kubernetes) for building scalable production-grade systems.
• Ability to analyze performance metrics, run experiments, and iteratively optimize systems for accuracy, latency, and reliability.
• Strong communication and collaboration skills, with the ability to work cross-functionally and explain complex technical concepts to non-technical stakeholders.
• Prior experience in applied NLP, search, recommendation engines, or AI-powered products is highly beneficial.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field, or equivalent practical experience.