Staff Operations AI Engineer

<div class="content-intro"><p><span style="font-weight: 400;"><strong>About Checkr<br></strong></span>Checkr is building the data platform to power safe and fair decisions. Over 140,000 companies and millions of people rely on Checkr for AI verification in the moments that matter most: getting a new job, a new place to live, a car ride, childcare, even a date. Customers include Uber, Pennymac, Airbnb, Doordash, and Anthropic.<br><br>We’re a team that thrives on solving complex problems with innovative solutions that advance our mission. Checkr is recognized on <a href="https://www.forbes.com/lists/cloud100/" target="_blank">Forbes Cloud 100 2025 List</a> and is a Y Combinator 2024 <a href="https://www.ycombinator.com/blog/yc-top-companies-2024">Breakthrough Company</a>.</p></div><h3><strong>About the Role</strong></h3> <p>We're looking for a Staff Operations AI Engineer who will architect, build, and refine the intelligent systems that power Checkr’s AI-driven operations. In this role, you'll be the technical expert responsible for designing the integrations, workflows, and data structures that enable AI Agents and automation to operate reliably at scale.</p> <p>You’ll work across system integration, workflow orchestration, application logic, data transformation, AI guardrails, and multi-platform automation—translating leadership’s strategic direction into high-quality technical execution. You’ll own complex, high-impact projects end-to-end, serve as a technical authority across teams, and develop robust systems that materially improve operational efficiency and AI performance.</p> <h3><strong>What You’ll Do</strong></h3> <p><strong>AI Agent Integration &amp; Automation Architecture</strong></p> <ul> <li>Design and own the integration architecture that enables AI Agents to operate safely and reliably across Checkr systems and third-party platforms.</li> <li>Build production-grade API integrations with secure authentication flows, webhook and event-driven patterns, and robust automation workflows that coordinate actions across tools like Zendesk, Salesforce, and internal services.</li> <li>Ensure AI-driven operations are resilient through strong error handling, retries, observability, and fallback mechanisms.</li> <li>Proactively identify integration gaps, system bottlenecks, and failure modes, and lead the technical solutions that improve reliability and scale.</li> </ul> <p><strong>Systems Engineering &amp; Data Foundations</strong></p> <ul> <li>Build and maintain the technical foundations that power AI-driven workflows, including structured data pipelines, normalized schemas, and predictable JSON inputs for LLMs.&nbsp;</li> <li>Establish engineering standards for workflow design, code quality, and system observability.&nbsp;</li> <li>Communicate architecture clearly through documentation and diagrams, and serve as a technical authority across teams to ensure consistent, high-quality execution.</li> </ul> <p><strong>AI Quality, Safety &amp; Guardrails</strong></p> <ul> <li>Implement guardrails, validation rules, and safety checks that ensure AI Agents act responsibly and accurately in production.&nbsp;</li> <li>Evaluate model output quality and continuously refine prompts, transformations, and logic to improve consistency, reliability, and trust in AI-driven decisions.</li> </ul> <h3><strong>What You Bring</strong></h3> <p><strong>Required Experience</strong></p> <ul> <li>5-7+ years in automation platforms, integration architecture, or AI-enabled operations</li> <li>Deep expertise in API design, OAuth/token-based authentication, webhooks, and event-driven systems</li> <li>Proven experience building reliable automation workflows with observability, retries, and failure handling</li> <li>Strong JavaScript and Python expertise for backend logic, scripting, and internal tooling</li> <li>Solid SQL experience for data transformation, validation, and operational analytics (Snowflake a plus)</li> <li>Advanced comfort with JSON, schemas, and data normalization for LLM and automation use cases</li> <li>Hands-on experience running LLM-powered agents or automations in production, including guardrails and output validation, with proven experience in prompt engineering frameworks</li> <li>Familiarity with integrating with CRM and support systems (e.g., Salesforce, Zendesk)</li> <li>An A-player mindset with a strong