Principal Engineer, Data Science AI Architect
Nagarro (company site, opens in a new tab)11+ yrsGurugramOn-siteDirect career pageEst. 30–55 LPA
Posted 2h ago
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Job description
Structured overview of role & requirements
About This Role
- Design, build, and run enterprise-scale Generative AI and Agentic AI solutions integrating with existing systems, ensuring security and budget compliance.
- Lead design and implementation of complex GenAI workflows combining LLMs, APIs, structured data, and user context, establishing engineering standards and reusable components across teams.
- Partner with stakeholders to translate business objectives into scalable AI architectures, review critical designs/codebases, resolve technical challenges, and ensure enterprise readiness including compliance and responsible AI practices.
Minimum Requirements
- Total work experience: 11+ years, with at least 5 years leading ML solutions from design to production.
- Strong expertise in ML fundamentals including model training, testing, deep learning basics, embeddings, classification, ranking, and regression/tabular ML with feature engineering and explainability.
- Proficient in Python, SQL, statistics (outlier detection, error metrics), time series forecasting, hierarchical forecasting, and prompt-injection testing.
- Experience with major cloud platforms (preferably Google Cloud services such as Vertex AI, BigQuery, Gemini) including pipelines, model registry, drift monitoring, retraining, and low-latency serving; Bachelor's or Master's degree in CS, IT, or related field.
Ideal Candidate Profile
- Demonstrated ability to translate ambiguous business problems into durable, scalable AI/ML architectures and solutions within enterprise environments.
- Experience leading cross-functional AI initiatives, setting engineering standards, conducting technical discovery, and guiding teams on complex GenAI and ML challenges.
- Deep hands-on experience with GenAI applications including LLMs, tool integration, retrieval-augmented generation, conversational agents, and responsible AI governance in cloud environments.