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# GenAI Engineer

- **Company:** Capgemini
- **Location:** New Brunswick, NJ, United States
- **Experience:** Experienced
- **Salary:** $90,000.0 - $110,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Information Engineering, DevOps, Python (Programming Language), Tensorflow, Azure Machine Learning, Data Processing, Pytorch, Large Language Models, Prompt Engineering, Generative AI, Scikit Learn, Information Technology, Databricks
- **Published:** August 16, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3355955833&tx=FL535FFL&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Bachelor's orMaster's degree in Computer Science, Data Science, ArtificialIntelligence, Engineering, or a related field.
 * Minimum 3years of professional experience and at least 2 years of experience inAI/ML development and deployment.
 * Proven experiencedesigning and implementing Generative AI solutions using LargeLanguage Models (LLMs) and modern GenAI frameworks.
 * Hands-onexperience with Azure Databricks for data processing, modeldevelopment, and operationalization.
 * Strongprogramming skills in Python .
 * Experience withmachine learning frameworks such as Scikit-learn, PyTorch, TensorFlow andXGBoost

## Description

* Design,develop, and deploy Generative AI solutions supporting HR use cases
 * Developscalable data science and machine learning pipelines using Azure MachineLearning and Azure Databricks
 * Designand implement Generative AI solutions leveraging Large Language Models (LLMs),Retrieval-Augmented Generation (RAG), prompt engineering, vector databases, andAI agents.
 * Collaboratewith Business Analysts, HR stakeholders, Product Owners, and SolutionArchitects to translate business challenges into measurable AI and GenAIsolutions.
 * Developand operationalize AI models with a strong focus on reproducibility,explainability, scalability, and performance.
 * UtilizeAzure DevOps, Azure ML, and Databricks to automate AI development anddeployment workflows.
 * Optimizetraining and inference workloads for performance, scalability, and costefficiency within Azure cloud environments.
 * Partnerclosely with Data Engineering teams to ensure high-quality, reliable, andfeature-ready datasets for AI and GenAI applications.


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