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GENERATIVE-AI ENGINEER (OMANI NATIONAL)

Nagarro

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This role on the market

113 open generative roles across 46 companies are on ApplySarthi right now, most of them in Pune (4), Bengaluru (4), Hyderabad (3).

What generative roles keep asking for: Generative AI (54%), Python (30%), AWS (26%), LLMs (20%), Machine learning (20%), RAG (17%), Azure (16%), Java (15%) — counted across their open postings here.

AWS jobs · Azure jobs · CI/CD jobs · Docker jobs

Nagarro has 881 open roles listed here.

Counted across 14 company job boards, updated as roles open and close.

Preparing for this interview

Interviews for generative roles keep coming back to Generative AI, Python, AWS, LLMs. Practise those questions before you sit with Nagarro.

Questions you are likely to be asked

  1. Why do you want to join Nagarro?
  2. What is your experience with Generative AI? Tell me one thing you learned the hard way.
  3. How would you explain your model's result to someone who is not technical?
  4. What would you check first if a model's accuracy dropped after going live?
  5. When would you not use machine learning for a problem?

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Must have Skills : Python (Strong), Model Packaging & Deployment (Strong), RAG Workflow (Strong), Prompt Engineering with LLMs (Strong) Good To Have Skills : Vector Databases and Embeddings (Capable) Job description: Generative AI developer (experience 1 to 2 years) Early-career AI/ML Engineer supporting the development and deployment of Generative AI solutions (LLMs, RAG systems). Focus on hands-on implementation, integration, and learning-by-delivery, under guidance. Must Have: 1. Strong foundation in Python (data handling, APIs, scripts) 2. Understanding of APIs, Docker, or deployment workflows 3. Exposure to deploying ML/AI models (even in projects/internships) 4. Understanding of embeddings, retrieval flow 5. Hands-on exposure through projects 6. Experience working with GPT/Llama APIs 7. Ability to structure prompts and evaluate outputs 8. Vector Databases (Exposure Level) - Familiarity with FAISS / Chroma / Pinecone and basic usage in projects. 9. . ML Fundamentals: Core concepts - overfitting, evaluation metrics, basic algorithms. Ability to reason about model behavior. Core Responsibilities (Execution Under Guidance) 1. Assist in building RAG-based GenAI solutions for enterprise use cases. 2. Develop Python-based services/APIs integrating LLMs. 3. Support data preprocessing, embeddings, and retrieval pipelines. 4. Contribute to model deployment and integration tasks. 5. Debug and improve existing pipelines under supervision. 6. Work closely with senior engineers to understand production constraints (latency, cost, accuracy) Good to Have 1. LangChain / LlamaIndex exposure 2. Cloud basics (Azure / AWS / GCP) 3. Basic understanding of CI/CD or MLOps concepts 4. Internship/project experience in GenAI or ML use cases Experience & Qualification 1. Bachelor's in Computer Science / Data Science or related field. 2. 12 years of experience in AI/ML (including internships and project work). 3. Exposure to at least one end-to-end ML/GenAI project (academic and professional).

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Listed on smartrecruiters · posted 2026-07-03. ApplySarthi collects openings and links to application pages; the role is advertised by Nagarro, not by us.