Sr AI Platform Engineer - Agent Integration & Tool

LPL Financial•Fort Mill, SC

1d•$115,154 - $191,889

About The Position

The Senior Engineer, Agent Integration & Tool Platform is responsible for designing and operating the enterprise platform that enables secure, governed, and reusable integration between AI agents, enterprise systems, APIs, applications, data products, and external services. This role will establish the standards, frameworks, and platform capabilities that allow development teams to rapidly onboard tools and services while maintaining enterprise requirements for security, governance, resiliency, observability, and auditability. The ideal candidate combines deep expertise in distributed systems, API architectures, platform engineering, and emerging agent interoperability standards to create a scalable foundation for enterprise AI ecosystems.

Requirements

Minimum of 8 years of software engineering experience.
Experience designing and building enterprise integration platforms, API platforms, or distributed systems.
Knowledge of API architecture, service contracts, event-driven systems, and platform engineering principles.
Experience implementing authentication, authorization, and governance controls in enterprise environments.
Experience building developer platforms, SDKs, shared services, or integration frameworks.
Designs and enables AI agent-to-tool communication frameworks, including tool discovery, service orchestration, and integration patterns that allow agents to securely access APIs, data sources, and enterprise services at scale.
Understanding of cloud-native architectures and modern software engineering practices.

Nice To Haves

Experience with agent frameworks, agent orchestration, or autonomous systems
Experience with Model Context Protocol (MCP), tool registries, service catalogs, or capability management platforms.
Experience with enterprise API management, service mesh, or integration platforms.
Familiarity with AI and machine learning platforms and their integration requirements.
Experience operating in highly regulated environments.

Responsibilities

Design and implement enterprise capabilities that enable AI agents to securely interact with enterprise systems, APIs, applications, and services.
Establish reusable integration patterns that accelerate adoption while reducing implementation complexity for development teams.
Define enterprise standards for agent interoperability and service integration.
Build and operate centralized capabilities for tool registration, discovery, metadata management, and lifecycle governance.
Establish standards for tool contracts, schemas, versioning, ownership, and operational support.
Develop mechanisms that enable agents and applications to discover and consume approved enterprise capabilities.
Define patterns and standards for communication and collaboration between autonomous and semi-autonomous systems.
Design mechanisms for agent capability discovery, delegation, orchestration, and coordination.
Establish governance and observability frameworks for multi-agent environments.
Implement controls supporting authentication, authorization, entitlement management, and policy enforcement.
Partner with Information Security, Risk, Compliance, and Enterprise Architecture teams to ensure integrations comply with enterprise standards.
Ensure all platform capabilities support auditability, traceability, and regulatory requirements.
Create SDKs, templates, onboarding frameworks, and reference implementations that simplify adoption.
Establish engineering standards and best practices for tool integration and agent development.
Improve developer productivity through automation, self-service capabilities, and platform abstractions.
Build capabilities supporting monitoring, tracing, usage analytics, performance management, and operational governance.
Establish metrics for tool adoption, reliability, utilization, and business impact.
Ensure platform resiliency, scalability, and operational excellence.
Lead architecture reviews and engineering design decisions.
Mentor engineers and influence technical direction across multiple teams.
Drive engineering excellence through best practices, reusable patterns, and platform modernization initiatives.