What are the responsibilities and job description for the Agentic AI Engineer position at Wall Street Consulting Services LLC?
Job Title: MCP Developer / AI Integration Engineer
Job Location: Warren NJ (Hybrid)
Employment Type: Contract
Qualifications
- 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