Agentic AI MCP Integration Specialist

Staffxpert Llc

Charlotte, NC, United States

about 1 month ago

Apply on www.careerjet.com

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

5 years minimum

Compensation

$74,900.0 - $112,300.0

Working hours

Regular working hours

Job source

www.careerjet.com

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Confluence JIRA Audit Trail User Authentication Cloud Computing Cyber Security Information Engineering Github Identity and Access Management

+33 more

Python (Programming Language) NoSQL OAuth OpenID Microsoft SharePoint Single Sign-On Software Engineering SQL Databases Systems Integration TypeScript Management of Software Versions Enterprise Application Integration Data Logging Enterprise Software Applications Large Language Models Snowflake Multi-Agent Systems Generative AI Information Technology Hashicorp Enterprise Integration Graphql Virtual Agents Api Design Restful APIs Pagination Network Server Webhooks Docker Jenkins Servicenow Databricks Microservices

Job description

Design, develop, and maintain Model Context Protocol (MCP) servers to expose enterprise tools, APIs, and data to AI agents.
Build reusable MCP connectors, APIs, and microservices for enterprise application integration.
Integrate AI agents with enterprise platforms including ServiceNow, Jira, Confluence, SharePoint, Snowflake, Databricks, SQL/NoSQL databases, CRM/ERP systems, and internal APIs.
Develop secure, scalable solutions using Python/TypeScript, REST APIs, GraphQL, and OAuth2/OIDC authentication.
Implement logging, monitoring, tracing, auditing, and security best practices for MCP services.
Define MCP tool schemas, prompt templates, and support single-agent and multi-agent workflows.
Collaborate with cloud, application, data, and cybersecurity teams to onboard enterprise systems into AI ecosystems.
Troubleshoot, optimize, and support production AI integrations while ensuring reliability, scalability, and compliance., * Design and implement MCP servers exposing enterprise tools (Rally, ServiceNow, Confluence, SharePoint, GitHub Jenkins, Snowflake, etc.).
Define tool schemas, resource URIs, and prompt templates following the MCP spec; ensure deterministic, idempotent, well-documented tools.
Implement authentication patterns (OAuth2, SSO, AWS IAM, service principals) and per-tenant authorization for MCP tools.
Build connectors and adapters that translate enterprise API quirks (pagination, rate limits, eventual consistency) into clean agent-facing primitives.
Instrument MCP servers with logging, tracing ,metrics, and audit trails for compliance.
Partner with the Architect on the MCP tool catalog, naming conventions, and versioning strategy.
Triage and resolve issues where agents misuse tools - improve schemas, descriptions, and error responses.
Deep understanding of the MCP specification (resources, tools, prompts, transports -/HTTP/SSE).
Strong API integration background: REST, webhooks, OAuth2/OIDC.
Python and/or TypeScript proficiency; familiarity with MCP SDKs in either ecosystem.
Enterprise integration patterns retries, circuit breakers, backoff, dead-letter queues.
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Requirements

5+ years of experience in software engineering, API integration, data engineering, or enterprise application integration.

Hands-on experience with Agentic AI, Generative AI/LLMs, and Model Context Protocol (MCP).

Experience building APIs, connectors, microservices, or enterprise integration layers. Experience integrating AI applications with ServiceNow, Jira, Confluence, SharePoint, GitHub, Jenkins, Snowflake, Databricks, SQL/NoSQL, CRM/ERP, and internal APIs. Experience with Docker, logging, monitoring, security, authentication, and observability.

Strong knowledge of REST APIs, GraphQL, OAuth2/OIDC, Webhooks, and enterprise integration patterns.

Experience designing MCP servers, APIs, microservices, and reusable enterprise connectors. Exposure to Agentic AI, tool-calling, workflow automation, or AI orchestration frameworks. Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, Data Science, or related field.