Engineer, Backend Integration & AI Transformation

EEOC Statement

“Lifepoint Health is an Equal Opportunity Employer. Lifepoint Health is committed to Equal Employment Opportunity for all applicants and employees and complies with all applicable laws prohibiting discrimination and harassment in employment.”

You must be authorized to work in the United States without employer sponsorship.WORK ENVIRONMENT AND TRAVEL REQUIREMENTS:

The position is: Remote

Travel Requirements: Less than 25%POSITION SUMMARY:

The Backend Integration Engineer is the connective tissue of the AI Transformation team. This engineer builds and maintains the API infrastructure and system integrations that allow AI agents to interact with the organization’s core enterprise platforms — including ServiceNow, Okta, ERP systems, and other business-critical tools. This role ensures that when an AI agent needs to take action in the real world, the pathways are secure, reliable, well-documented, and reusable.

This is a role for a solid backend developer who is excited to apply strong fundamentals in an AI-first context. Experience with enterprise platform APIs is a strong differentiator. Direct MCP server development experience is rare and not required — a willingness to become an internal expert is expected.

ESSENTIAL FUNCTIONS:

• Design, build, and maintain RESTful and event-driven APIs that expose enterprise system capabilities to AI agents and agentic workflows in a secure and controlled manner.
• Develop and maintain Model Context Protocol (MCP) server implementations that provide AI agents with structured, secure, and auditable access to enterprise tools, data sources, and services.
• Build and manage integrations with key enterprise platforms including ServiceNow (workflow triggers, CMDB queries, ticket management), Okta (identity and access queries, group management), and ERP/financial systems.
• Implement security controls for all integration endpoints: OAuth 2.0 / OIDC authentication, API gateway policies, rate limiting, input sanitization, payload validation, and comprehensive audit logging.
• Collaborate with Agentic AI Engineers to define MCP tool specifications and ensure agents can reliably invoke enterprise actions with appropriate authorization checks and operational guardrails.
• Maintain comprehensive API documentation and an integration catalog so the team can build on existing ‘paved paths’ rather than re-implementing integrations from scratch.
• Monitor integration health, SLA adherence, and error rates; implement alerting and graceful degradation patterns so agent failures are isolated and recoverable.
• Work with the AI governance team to ensure integration designs comply with data classification policies, access control requirements, and applicable regulatory standards.