Join Cloudary as an AI/ML Engineer to drive critical initiatives forward rapidly as an agile, embedded expert.

Requirements

4+ years of software engineering experience
2+ years integrating ML or LLM models into production systems
Strong proficiency in Python with ML frameworks (PyTorch, TensorFlow, or scikit-learn)
Hands-on experience with Generative AI, RAG architectures, and agentic AI frameworks (LangChain, LangGraph, or equivalent)
Ability to integrate AI services into an existing.NET / C# / SQL Server backend without a full rewrite
Experience with containerized deployment using Docker and Kubernetes
Experience with REST API design connecting AI systems to third-party services and internal platforms
Comfortable working within a CI/CD pipeline managed through Azure DevOps and Git
Experience with workflow orchestration tools (Temporal, Step Functions, Airflow, or similar)
Strong MLOps understanding: model versioning, CI/CD, monitoring, and production incident response
Hands-on experience with AI systems for insurance claims, fleet management, or a closely related domain (P&C, auto, or commercial lines)
Working knowledge of the claims lifecycle: intake, investigation, adjudication, settlement, and recovery
Familiarity with claims management systems and integration patterns used in insurance environments

Join Cloudary as an AI/ML Engineer to drive critical initiatives forward rapidly as an agile, embedded expert.

4+ years of software engineering experience
2+ years integrating ML or LLM models into production systems
Strong proficiency in Python with ML frameworks (PyTorch, TensorFlow, or scikit-learn)
Hands-on experience with Generative AI, RAG architectures, and agentic AI frameworks (LangChain, LangGraph, or equivalent)
Ability to integrate AI services into an existing.NET / C# / SQL Server backend without a full rewrite
Experience with containerized deployment using Docker and Kubernetes
Experience with REST API design connecting AI systems to third-party services and internal platforms
Comfortable working within a CI/CD pipeline managed through Azure DevOps and Git
Experience with workflow orchestration tools (Temporal, Step Functions, Airflow, or similar)
Strong MLOps understanding: model versioning, CI/CD, monitoring, and production incident response
Hands-on experience with AI systems for insurance claims, fleet management, or a closely related domain (P&C, auto, or commercial lines)
Working knowledge of the claims lifecycle: intake, investigation, adjudication, settlement, and recovery
Familiarity with claims management systems and integration patterns used in insurance environments

AI/ML Engineer Azure