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).
Skills Required
- Strong Python (data handling, APIs, scripting)
- Model packaging and deployment experience (Docker, deployment workflows)
- RAG workflow experience (retrieval-augmented generation)
- Prompt engineering and experience with LLMs (GPT/Llama)
- Understanding of APIs and integration of LLMs into services/APIs
- Exposure to deploying ML/AI models (projects or internships)
- Understanding of embeddings and retrieval flow
- Familiarity with vector databases (FAISS, Chroma, Pinecone)
- ML fundamentals (overfitting, evaluation metrics, basic algorithms)
- Hands-on project experience with GenAI/ML (academic or professional)
- Experience working with GPT and Llama APIs
- Bachelor's degree in Computer Science, Data Science, or related field
- 1-2 years experience in AI/ML (including internships and project work)
- Exposure to LangChain or LlamaIndex
- Basic cloud knowledge (Azure, AWS, or GCP)
- Basic CI/CD or MLOps understanding
Nagarro Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Nagarro and has not been reviewed or approved by Nagarro.
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Pay Growth & Progression — Compensation is at times described as competitive, with salary hikes and perks occurring on certain occasions. Better growth opportunities and compensation are also positioned as an advantage versus other service-based companies.
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Flexible Benefits — Work arrangements are framed around a “work-from-anywhere” mindset with flexitime and family-friendly working models. This flexibility appears to add meaningful value to the overall rewards package for many roles.
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Healthcare Strength — Medical, dental, and vision coverage are described as available for employees and dependents, alongside life insurance. Mental-health support is also included via an Employee Assistance Program (EAP).
Nagarro Insights
What We Do
Nagarro helps future-proof your business through a forward-thinking, fluidic, and CARING mindset. We excel at digital engineering and help our clients become human-centric, digital-first organizations, augmenting their ability to be responsive, efficient, intimate, creative, and sustainable. Today, we are 19,000 experts across 36 countries, forming a Nation of Nagarrians, ready to help our customers succeed.
