DATA 部門 - AI Engineer

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

Job Description

Capgemini Japan is seeking an experienced AI Engineer to join our Insights and Data team. This role sits at the intersection of a large-scale insurance data ecosystem—covering customer, agent, transaction, and policy data—and advanced AI-driven intelligence.

The successful candidate will design, build, and deploy scalable Generative AI and Predictive Analytics solutions that transform our Azure-based data lake into actionable insights and automated, intelligent experiences. You will work closely with data engineers, platform teams, and business stakeholders to operationalize AI at enterprise scale.

Key Responsibilities

AI & Model Development

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 and production-ready AI solutions.

Data Integration & Collaboration

Partner with data engineering teams to ingest and process high-volume datasets (Parquet, CSV, text) from Azure Data Lake Storage (ADLS) and Azure Synapse Analytics.

Ensure seamless integration between data pipelines and AI workflows.

Application Architecture

Develop serverless orchestration layers using Azure Functions to connect AI models with downstream applications and APIs.

Support real-time and batch inference use cases.

Search & Storage Optimization

Use Azure AI Search to enable low-latency retrieval for AI outputs, embeddings, and metadata.

Contribute to efficient data and metadata storage strategies.

Operational Excellence & MLOps

Implement MLOps best practices, including model versioning, monitoring, and lifecycle management.

Integrate AI workflows into CI/CD pipelines to enable automated testing and deployment.

Job Description - Grade Specific

Technical Requirements

Azure AI & Cloud Stack

Hands-on experience with Azure Machine Learning, Azure AI Foundry, and Azure OpenAI Service.

Data & Analytics

Strong understanding of Azure Data Lake Storage (ADLS) and Azure Synapse Analytics.

Experience working with Parquet files and large-scale, enterprise data environments.

Programming & Frameworks

Proficiency in Python for AI/ML development.

Working knowledge of Scala and Apache Spark, aligning with enterprise ETL platforms.

Backend & Storage

Experience building serverless solutions using Azure Functions.

Familiarity with Azure Cosmos DB or other NoSQL data stores.

DevOps & Automation

Knowledge of CI/CD tooling such as Azure DevOps or GitHub Actions to automate AI and ML workflows.

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.

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 our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of €22.1 billion.

Make it real | www.capgemini.com