GENERATIVE-AI ENGINEER (OMANI NATIONAL)

Nagarro; Muscat; On-site; OMR 16,000 - 23,000; Full time

Job summary

Nagarro is seeking a Generative AI developer with 1–2 years of experience to support the development and deployment of GenAI solutions (LLMs, RAG systems) in Muscat, Oman.

The role emphasizes hands-on implementation, integration, and learning-by-delivery under guidance, focusing on Python services, embeddings, and model deployment. Collaborative work with senior engineers is expected.

Qualifications

• Bachelor's in Computer Science, Data Science or related field.
• 1–2 years of Generative AI/ML experience.
• Exposure to end-to-end GenAI/ML projects (academic or professional).
• Strong Python data handling, APIs and scripting foundations.
• Experience deploying ML/AI models and embeddings pipelines.
• Familiarity with vector databases and retrieval flows.
• Hands-on exposure through projects and internship work.

Responsibilities

• Assist in building RAG-based GenAI solutions for enterprise use cases.
• Develop Python-based services/APIs integrating LLMs.
• Support data preprocessing, embeddings, and retrieval pipelines.
• Contribute to model deployment and integration tasks.
• Debug and improve existing pipelines under supervision.
• Work with senior engineers to understand production constraints (latency, cost, accuracy).

Skills

Python

Model deployment

RAG workflows

Prompt engineering

LLM APIs

Docker

APIs

Education

Bachelor's in Computer Science / Data Science

Tools

Docker

LangChain

LlamaIndex

FAISS

Pinecone

Job description

Job Description

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).