AI Engineer
Description
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
Skills
- AI
- Analytics
- API
- Automation
- Azure
- Azure DevOps
- Azure Functions
- Azure Synapse
- CI/CD
- Cloud
- Cosmos Db
- Data Engineering
- Data Lake
- Data Pipelines
- Databricks
- DevOps
- Embeddings
- ETL
- Generative AI
- GitHub
- GitHub Actions
- LLM
- Machine Learning
- MLOps
- NoSQL
- OpenAI
- Parquet
- Predictive Analytics
- Python
- RAG
- Scala
- Serverless
- Spark
- Test Automation