Senior Staff Engineer, Generative AI

👋🏼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 (18000+ experts across 40 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! REQUIREMENTS: - Total experience 8+ years. - Deep understanding of LLMs (e.g., GPTs, Llama, Claude, Gemini, Qwen, Mistral, BERT-family models) and their architectures (Transformers) - Should have expert-level prompt engineering skills and proven experience implementing RAG patterns - High proficiency in Python and standard AI/ML libraries (e.g., LangChain, LlamaIndex, LangGraph, LangSmith, Hugging Face Transformers, Scikit-learn, PyTorch/TensorFlow). - Experience implementing RAG architectures and prompt engineering. - Strong experience with fine-tuning and distillation techniques and evaluation. - Must have experience in Python, SQL, Pandas, SciPy, and Scikit-learn, ML model development, validation, deployment, and tuning - Should have done anomaly-detection implementation - Must have experience with Snowflake Data Cloud and Snowflake Cortex AI. - Strong experience using managed AI/ML services on the target cloud platform (e.g., Azure Machine Learning Studio, AI Foundry). - Strong understanding of vector databases (e.g., Weaviate, Neo4j) - Should have understanding of GenAI evaluation metrics (e.g., BLEU, ROUGE, perplexity, semantic similarity, human evaluation). - Architect and implement scalable GenAI and Agentic AI solutions end-to-end. - Should be able to write high-quality, production-ready Python code with strong testing and maintainability practices. - Should be able to productionize AI systems on Azure or AWS, ensuring enterprise-grade reliability and performance. - Should be able to build and expose APIs using FastAPI, integrating with databases through an ORM. - Should be able to scale GenAI solutions to support enterprise workloads. - Collaborate across product and engineering teams to convert business needs into AI-driven solutions. - Strong ability to both architect and code GenAI/Agentic AI solutions. - Proven production experience with GenAI deployments on Azure or AWS. - Strong experience in scaling AI solutions in live environments. - Should have successfully delivered at least one production GenAI/Agentic AI solution. - Should have familiarity with Model Context Protocol (MCP). - Should have contributions to open-source GenAI projects. - Excellent communication skills and the ability to collaborate effectively with cross-functional teams.RESPONSIBILITIES: - Understanding the client’s business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements. - Mapping decisions with requirements and be able to translate the same to developers. - Identifying different solutions and being able to narrow down the best option that meets the clients’ requirements. - Defining guidelines and benchmarks for NFR considerations during project implementation. - Writing and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers. - Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed. - Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it. - Understanding and relating technology integration scenarios and applying these learnings in projects. - Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken. - Carrying out POCs to make sure that suggested design/technologies meet the requirements. Bachelor’s or master’s degree in computer science, Information Technology, or a related field.