AI Platform Engineer

Core States Group•Philadelphia, PA

5d•$140,000 - $165,000•Hybrid

About The Position

The AI Platform Engineer will be a member of the Digital Transformation team at Core States and report to the Director of that group. The AI Platform Engineer will be responsible for building and maintaining the connectivity layer that makes the firm’s core systems accessible to AI, including integration services and MCP servers for business intelligence, ERP, design, and document management platforms, along with the authentication, logging, and evaluation infrastructure those integrations depend on. High-level architecture is owned by the Director of Digital Transformation; this role advises on design, implements it, and tests it rigorously. They will be expected to build integration services against enterprise APIs, implement per-user authorization so AI tools respect the permissions already defined in each source system, establish the auditing and benchmarking practices that keep AI-generated answers trustworthy, and support AI-enabled features in the team’s internal applications.

Requirements

Bachelors degree in Business, Information Technology, Engineering, or relevant field; or equivalent professional experience
5+ years of professional software development experience, with significant time spent on backend services and system integration
Demonstrated experience integrating enterprise systems through REST APIs, including authentication, pagination, rate limiting, and error handling
Experience implementing OAuth 2.0 and OpenID Connect flows in a Microsoft Entra ID environment, including delegated and on-behalf-of scenarios
Experience building, deploying, and operating services in Microsoft Azure
Hands-on experience integrating LLM APIs into production software (OpenAI, Anthropic, or comparable)
Strong C# and .NET Core development skills; Python or TypeScript for integration and tooling work
Working knowledge of REST API design and consumption, OAuth 2.0 and OpenID Connect, and secure token handling
Microsoft Entra ID application registrations, app roles, scopes, consent, and the implications of Conditional Access policies
SQL Server and relational data modeling, including comfort assessing query performance
Azure services relevant to hosting integration workloads, such as App Service, Functions, Key Vault, API Management, and Application Insights
Familiarity with the Model Context Protocol and tool and function-calling patterns, retrieval-augmented generation concepts, and prompt and version management
Source control, CI/CD, and infrastructure-as-code practices (Azure DevOps, GitHub Actions, Bicep or Terraform)

Nice To Haves

Experience with MCP server development, or comparable tool and function-calling integration work, preferred
Experience building automated test suites or evaluation harnesses for systems with non-deterministic output preferred
Experience in the AEC industry or another project-based professional services business preferred
Familiarity with the APIs of relevant enterprise platforms preferred, including Power BI and Fabric, Deltek Vantagepoint, Autodesk Platform Services, Egnyte, and Microsoft Graph

Responsibilities

Design, build, and maintain integration services and MCP servers that expose firm systems — including Power BI and Fabric, Deltek Vantagepoint, Autodesk Platform Services, Egnyte, and internal applications — to approved AI platforms
Implement per-user authorization so AI access respects the permissions already defined in each source system, using Microsoft Entra ID and OAuth 2.0 delegated and on-behalf-of flows
Build audit logging, monitoring, and access reporting for AI-to-system traffic
Establish evaluation and benchmarking infrastructure, including automated tests for connector correctness, regression testing of model-facing behavior, and ongoing measurement of answer accuracy
Evaluate vendor-supplied connectors and MCP servers against in-house development, and make clear build-versus-adopt recommendations
Implement and maintain the entity resolution and crosswalk services that link records across systems, working from the semantic model defined with the Director of Digital Transformation and the data engineer
Advise on architectural decisions by surfacing tradeoffs, risks, and implementation constraints for the Director of Digital Transformation to decide
Develop and support AI-enabled features in internal applications, including LLM API integration, structured outputs, and prompt and version management
Write and maintain automated tests, technical documentation, and deployment automation for all platform components
Partner with the Technical Program Manager on scope, estimates, and delivery commitments, and with system owners on data access and governance questions
Other duties as assigned