AI Engineer - Insurance Domain - HYBRID
Tasks
- Architect and implement autonomous AI agents
- Build and maintain MLOps pipelines
- Build retrieval augmented generation RAG pipelines
- Create technical documentation for solutions and deployments
- Deploy models as REST APIs or batch inference
- Design fine tune deploy LLMs for insurance use cases
- Develop guardrails monitoring and audit logging
- Develop prompt engineering frameworks and evaluation pipelines
- Establish model monitoring for drift and anomalies
- Implement CI/CD pipelines for ML models
- Implement human in the loop HITL checkpoints
- Integrate LLMs with internal data platforms
- Manage model registry and lineage tracking
- Mentor junior engineers
- Participate in agile scrum ceremonies
- Translate domain requirements into AI solution designs
Perks/Benefits
- N/A
Skills/Tech-stack
AI Search | Agile Scrum | Apache Airflow | Autonomous Agents | Azure AI | Azure AI Search | Azure Container | Azure Container Apps | Azure DevOps | Azure Kubernetes | Azure Kubernetes Service | Azure Logic | Azure Logic Apps | Azure Machine Learning | Batch inference | Bias Mitigation | ChromaDB | Container Apps | Data Drift | Databricks | Databricks Workflows | Explainability | Fairness | Feature Engineering | Feature Store | GitHub Actions | Kubernetes Service | Langchain | Language Models | Large Language Models | Lineage Tracking | Llamaindex | Logic Apps | MLflow | Machine Learning | Model Monitoring | Model Registry | Pinecone | Prompt engineering | REST APIs | React | Responsible AI | Retrieval-Augmented Generation | Semantic Kernel | Tool-augmented agents | Vector Databases
Education
Roles
AI | AI Engineer | Engineer
Regions
Countries
States
Cities
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