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Open nowPosted 193 days ago

AI Engineer

Nexus Corporation224 open roles

Where
Tokyo
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Your applicationOpen nowAI EngineerNexus Corporation · Tokyo

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: posted 193 days ago

The posting

We are 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. 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: Experience in the Insurance or Financial Services domain 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

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