Sr. Analyst, Platform Standards & API

Lincoln Financial•Radnor, PA

4d•$96,900 - $176,200•Hybrid

About The Position

The Platform Standards & API Lead turns Lincoln's target cloud and AI architecture into an enforceable set of engineering standards, governed APIs, and self-service tooling that every team, and every vendor, builds on. The role owns the full API and data-contract lifecycle from design through deprecation, establishes secure patterns for how AI/GenAI applications reach enterprise data and models, and acts as the cross-functional owner when standards break down: running structured issue intake, trend analysis, and incident reporting so problems get fixed at the pattern level, not just the instance level.

Requirements

4 Year/Bachelor's degree or equivalent work experience (4 years of experience in lieu of Bachelor's) (Minimum Required)
5+ years in API/platform architecture roles, with direct experience publishing a documented engineering-standards artifact and owning an API platform where other teams are the primary customers.
Experience with data-contract patterns, schema governance, versioning/deprecation policy, and REST (GraphQL a plus) API design at enterprise scale.
Strong Python skills and working knowledge of cloud data services (Glue, Lake Formation, Athena) and AI/agent stacks (Bedrock, AgentCore, MCP).
Able to work from a target architecture and turn it into rules developers actually follow.

Responsibilities

Author and maintain the platform's data/API engineering standards: endpoint design, data-contract shape, versioning, backward compatibility, and deprecation policy across the full API lifecycle.
Own the Data Contracts standard (publish/consume model) that every data product must meet, starting with existing structured-data and existing APIs.
Establish governance for how AI/GenAI applications securely access enterprise data and models, including Model Context Protocol (MCP) patterns, so teams can build AI features without bypassing platform controls.
Define guardrails that prevent AI/GenAI services from leaking sensitive data or operating outside approved bounds, in partnership with governance and security teams.
Build self-service developer tooling (templates, onboarding paths, schema-validation and observability tooling) so teams can adopt platform standards without needing hands-on platform-team support for every integration.
Own structured intake and triage for standards violations, API incidents, and integration issues; identify recurring patterns and drive them to root-cause fixes rather than one-off patches.
Report standards adoption, API health, and incident trends to engineering and platform leadership.
Partner with governance and enterprise-catalog teams so platform-side standards (schemas, metadata tagging) satisfy governance requirements.
Mentor engineers across the platform on API design and standards adoption.