Job
Description
Role Overview: As an MCP Developer in commercial P&C insurance, your primary focus will be on developing systems and integrations using the Model Context Protocol (MCP) to leverage Artificial Intelligence (AI) and Large Language Models (LLMs) within insurance operations. You will play a crucial role in building the infrastructure that enables AI agents to securely access and act upon internal P&C data sources, enhancing automation and decision-making in core insurance functions like underwriting and claims processing. Key Responsibilities: - Develop and implement robust integrations between AI models (LLMs) and internal data repositories and business tools using the Model Context Protocol (MCP). - Build and maintain MCP servers and clients to expose necessary data and capabilities to AI agents. - Design and implement agentic workflows for AI systems to perform complex, multi-step tasks such as accessing real-time policy data and processing claims information. - Implement secure coding practices and ensure compliance with insurance industry regulations and internal standards for data privacy and secure data handling. - Work with existing APIs (REST/SOAP) and develop new ones to facilitate data flow to and from the MCP environment. - Collaborate with actuaries, underwriters, claims specialists, and IT teams to identify AI opportunities and deploy seamless solutions. - Perform testing to ensure accurate and reliable AI-driven job outputs and maintain high performance levels. - Document all development processes, system architectures, and operational procedures for MCP integrations. Qualifications Required: - 3+ years of experience in software development or AI integration, preferably within the insurance or financial services industry. - Strong knowledge of Commercial P&C insurance products, underwriting processes, and claims systems. - Proficiency in programming languages like Python, Java, or similar. - Experience with API development and management. - Familiarity with cloud platforms (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes). - Understanding of the Model Context Protocol (MCP) specification and SDKs. Role Overview: As an MCP Developer in commercial P&C insurance, your primary focus will be on developing systems and integrations using the Model Context Protocol (MCP) to leverage Artificial Intelligence (AI) and Large Language Models (LLMs) within insurance operations. You will play a crucial role in building the infrastructure that enables AI agents to securely access and act upon internal P&C data sources, enhancing automation and decision-making in core insurance functions like underwriting and claims processing. Key Responsibilities: - Develop and implement robust integrations between AI models (LLMs) and internal data repositories and business tools using the Model Context Protocol (MCP). - Build and maintain MCP servers and clients to expose necessary data and capabilities to AI agents. - Design and implement agentic workflows for AI systems to perform complex, multi-step tasks such as accessing real-time policy data and processing claims information. - Implement secure coding practices and ensure compliance with insurance industry regulations and internal standards for data privacy and secure data handling. - Work with existing APIs (REST/SOAP) and develop new ones to facilitate data flow to and from the MCP environment. - Collaborate with actuaries, underwriters, claims specialists, and IT teams to identify AI opportunities and deploy seamless solutions. - Perform testing to ensure accurate and reliable AI-driven job outputs and maintain high performance levels. - Document all development processes, system architectures, and operational procedures for MCP integrations. Qualifications Required: - 3+ years of experience in software development or AI integration, preferably within the insurance or financial services industry. - Strong knowledge of Commercial P&C insurance products, underwriting processes, and claims systems. - Proficiency in programming languages like Python, Java, or similar. - Experience with API development and management. - Familiarity with cloud platforms (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes). - Understanding of the Model Context Protocol (MCP) specification and SDKs.
