

Wall Street Consulting Services LLC
MCP Developer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an MCP Developer with a long-term contract in Warren, NJ, offering a competitive pay rate. Key skills required include 3+ years in software development, AI integration, and strong knowledge of commercial P&C insurance. Proficiency in Python, Java, and API management is essential.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
December 14, 2025
🕒 - Duration
Unknown
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🏝️ - Location
Hybrid
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Warren, NJ
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🧠 - Skills detailed
#Deployment #Azure #Data Processing #Docker #Databases #Cloud #Quality Assurance #Data Privacy #Automation #Kubernetes #AWS (Amazon Web Services) #GCP (Google Cloud Platform) #API (Application Programming Interface) #Programming #Python #Documentation #AI (Artificial Intelligence) #Compliance #Java #Security #REST (Representational State Transfer)
Role description
Job Description:
Title: AI Engineer or MCP Developer
Location: Hybrid role in Warren, NJ
Duration: Long Term Contract
Kindly share your resumes to dkannoji@wscs.ai
Description: A MCP Developer in commercial P&C insurance is typically an IT role focused on developing systems and integrations using the Model Context Protocol (MCP) to leverage Artificial Intelligence (AI) and Large Language Models (LLMs) within insurance operations. This role involves building the infrastructure that allows AI agents to securely and reliably access and act upon internal P&C data sources (e.g., policy systems, claims databases, underwriting documents), thereby enhancing automation and decision-making in core insurance functions like underwriting and claims processing.
Responsibilities:
• AI Integration: Develop and implement robust integrations between AI models (LLMs) and internal data repositories and business tools using the Model Context Protocol (MCP).
• System Development: Build and maintain MCP servers and clients to expose necessary data and capabilities to AI agents.
• Workflow Automation: Design and implement agentic workflows that allow AI systems to perform complex, multi-step tasks, such as accessing real-time policy data, processing claims information, and updating customer records.
• Security & Compliance: Implement secure coding practices and ensure all AI interactions and data exchanges via MCP adhere to insurance industry regulations and internal compliance standards (e.g., data privacy, secure data handling).
• API Management: Work with existing APIs (REST/SOAP) and develop new ones to facilitate data flow to and from the MCP environment.
• Collaboration: Partner with actuaries, underwriters, claims specialists, and IT teams to identify AI opportunities and ensure seamless solution deployment.
• Testing & Quality Assurance: Perform testing to ensure AI-driven job outputs are accurate and reliable, and maintain high performance levels.
• Documentation: Document all development processes, system architectures, and operational procedures for MCP integrations.
• Experience: 3+ years of experience in software development or AI integration, preferably within the insurance or financial services industry.
• P&C Knowledge: Strong knowledge of Commercial P&C insurance products, underwriting processes, and claims systems is highly preferred.
Technical Expertise:
• 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
Job Description:
Title: AI Engineer or MCP Developer
Location: Hybrid role in Warren, NJ
Duration: Long Term Contract
Kindly share your resumes to dkannoji@wscs.ai
Description: A MCP Developer in commercial P&C insurance is typically an IT role focused on developing systems and integrations using the Model Context Protocol (MCP) to leverage Artificial Intelligence (AI) and Large Language Models (LLMs) within insurance operations. This role involves building the infrastructure that allows AI agents to securely and reliably access and act upon internal P&C data sources (e.g., policy systems, claims databases, underwriting documents), thereby enhancing automation and decision-making in core insurance functions like underwriting and claims processing.
Responsibilities:
• AI Integration: Develop and implement robust integrations between AI models (LLMs) and internal data repositories and business tools using the Model Context Protocol (MCP).
• System Development: Build and maintain MCP servers and clients to expose necessary data and capabilities to AI agents.
• Workflow Automation: Design and implement agentic workflows that allow AI systems to perform complex, multi-step tasks, such as accessing real-time policy data, processing claims information, and updating customer records.
• Security & Compliance: Implement secure coding practices and ensure all AI interactions and data exchanges via MCP adhere to insurance industry regulations and internal compliance standards (e.g., data privacy, secure data handling).
• API Management: Work with existing APIs (REST/SOAP) and develop new ones to facilitate data flow to and from the MCP environment.
• Collaboration: Partner with actuaries, underwriters, claims specialists, and IT teams to identify AI opportunities and ensure seamless solution deployment.
• Testing & Quality Assurance: Perform testing to ensure AI-driven job outputs are accurate and reliable, and maintain high performance levels.
• Documentation: Document all development processes, system architectures, and operational procedures for MCP integrations.
• Experience: 3+ years of experience in software development or AI integration, preferably within the insurance or financial services industry.
• P&C Knowledge: Strong knowledge of Commercial P&C insurance products, underwriting processes, and claims systems is highly preferred.
Technical Expertise:
• 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






