AI Engineer

Responsibilities

• Design, train, and deploy predictive machine learning models and LLM-powered applications, including Retrieval-Augmented Generation (RAG) systems.
• Leverage Azure Machine Learning and Azure AI Foundry to build scalable, production-ready AI solutions.
• Partner with data engineering teams to process high-volume datasets from Azure Data Lake Storage (ADLS) and Azure Synapse Analytics.
• Develop serverless orchestration layers using Azure Functions to connect AI models with downstream applications and APIs.
• Implement MLOps best practices, including model versioning, monitoring, and lifecycle management.
• Integrate AI workflows into CI/CD pipelines to enable automated testing and deployment.

Requirements

• Hands-on experience with Azure Machine Learning, Azure AI Foundry, and Azure OpenAI Service.
• Strong understanding of Azure Data Lake Storage (ADLS) and Azure Synapse Analytics.
• Proficiency in Python for AI/ML development.
• Working knowledge of Scala and Apache Spark.
• Experience building serverless solutions using Azure Functions.
• Familiarity with Azure Cosmos DB or other NoSQL data stores.
• Knowledge of CI/CD tooling such as Azure DevOps or GitHub Actions.

Preferred Qualifications

• Prior experience in the Insurance or Financial Services domain.
• Proven ability to extract actionable insights from complex customer and transactional datasets.
• Hands-on experience designing and implementing RAG-based AI systems.
• Familiarity with distributed data processing using Azure Databricks.

About the Company

Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With a strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries.