Senior Staff Engineer (GenAI Vector Database & RAG Specialist)

Job description

Company Description We're Nagarro. We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale across all devices and digital mediums, and our people exist everywhere in the world (17500+ experts across 39 countries, to be exact). Our work culture is dynamic and non-hierarchical. We're looking for great new colleagues. That's where you come in! Job Description REQUIREMENTS: • Strong experience in Data & AI, with hands on experience in AI/ML data platforms, semantic search, vector databases, or GenAI solutions. • Strong hands-on experience designing and deploying production-grade RAG solutions. • Strong hands-on experience with vector databases, preferably Oracle Database 26ai / Oracle AI Vector Search, Milvus, or alternatives such as Pinecone, Weaviate, Qdrant, or pgVector. • Strong expertise in Python, SQL, and data engineering. • Solid understanding of RAG architecture, embeddings, semantic search, vector similarity search, hybrid search, reranking, and LLM integration. • Experience building scalable data pipelines for structured and unstructured data. • Experience with APIs, CI/CD, containers, and cloud/on-premises platforms. • Strong understanding of data governance, data quality, metadata, lineage, security, access controls, compliance, and audit requirements. • Experience with production platform monitoring, observability, performance optimization, and operational controls. • Experience establishing enterprise-scale AI/GenAI data platforms and reusable engineering standards. • Preferred experience in banking, financial services, or other regulated industries. • Familiarity with LangChain, LlamaIndex, Databricks, Spark, Kafka, and Airflow is preferred. RESPONSIBILITIES: • Writing and reviewing great quality code. • Design, build, and manage the enterprise vector database platform and retrieval services supporting AI and GenAI use cases. • Design and implement end-to-end RAG pipelines, including ingestion, preprocessing, chunking, embedding generation, indexing, retrieval, and reranking. • Develop and maintain scalable data pipelines for structured and unstructured enterprise data. • Implement data quality, metadata management, lineage, security, access controls, and audit controls across AI data platforms. • Optimize vector search and retrieval solutions for accuracy, performance, scalability, latency, and reliability. • Implement monitoring, observability, alerting, and operational processes for production vector database and RAG platforms. • Establish enterprise-wide governance standards, reusable frameworks, architecture patterns, and best practices for AI/GenAI use cases. • Integrate vector databases and retrieval services with LLMs, AI applications, APIs, and enterprise data platforms. • Collaborate with data scientists, ML engineers, application developers, architects, security teams, and governance teams to deliver enterprise AI solutions. • Evaluate vector database technologies and recommend appropriate solutions based on performance, scalability, security, cost, and business requirements. • Establish the enterprise vector database and RAG capability from the ground up, including architecture, development standards, deployment patterns, governance, and operational controls. • Ensure solutions meet enterprise requirements for security, compliance, reliability, maintainability, and auditability. • Envisioning the overall solution for defined functional and non-functional requirements, and being able to define technologies, patterns and frameworks to realize it. • Determining and implementing design methodologies and tool sets. • Being able to lead/support UAT and production roll outs. • Creating, understanding and validating WBS and estimated effort for given module/task, and being able to justify it. • Addressing issues promptly, responding positively to setbacks and challenges with a mindset of continuous improvement. • Giving constructive feedback to the team members and setting clear expectations. • Helping the team in troubleshooting and resolving of complex bugs. • Coming up with solutions to any issue that is raised during code/design review and being able to justify the decision taken. Qualifications Bachelor’s or master’s degree in computer science, Information Technology, or a related field.