Staff Operations AI Engineer
Checkr · Denver, Colorado, United States; Nashville, Tennessee, United States
About this role
**Staff Operations AI Engineer — Checkr** **About Checkr** 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, and more. Customers include Uber, Pennymac, Airbnb, DoorDash, and Anthropic. **About the Role** We’re looking for a **Staff Operations AI Engineer** to architect, build, and refine the intelligent systems that power Checkr’s AI-driven operations. You’ll design **integrations, workflows, and data structures** that enable **AI Agents and automation** to operate reliably at scale. You’ll work across system integration, workflow orchestration, application logic, data transformation, AI guardrails, and multi-platform automation—turning leadership’s strategy into high-quality technical execution. You’ll own complex, high-impact projects end-to-end and serve as a technical authority across teams. --- ## What You’ll Do ### AI Agent Integration & Automation Architecture - Design and own the integration architecture that enables AI Agents to operate safely and reliably across Checkr systems and third-party platforms. - Build production-grade API integrations with secure authentication flows, webhook/event-driven patterns, and robust automation workflows coordinating actions across tools like **Zendesk**, **Salesforce**, and internal services. - Ensure AI-driven operations are resilient with strong error handling, retries, observability, and fallback mechanisms. - Identify integration gaps, bottlenecks, and failure modes—and lead technical solutions to improve reliability and scale. ### Systems Engineering & Data Foundations - Build and maintain technical foundations for AI-driven workflows, including structured data pipelines, normalized schemas, and predictable JSON inputs for LLMs. - Establish engineering standards for workflow design, code quality, and system observability. - Communicate architecture clearly via documentation and diagrams; act as a technical authority to ensure consistent, high-quality execution. ### AI Quality, Safety & Guardrails - Implement guardrails, validation rules, and safety checks so AI Agents act responsibly and accurately in production. - Evaluate model output quality and continuously refine prompts, transformations, and logic to improve consistency, reliability, and trust. --- ## What You Bring ### Required Experience - **5–7+ years** in automation platforms, integration architecture, or AI-enabled operations. - Deep expertise in **API design**, **OAuth/token-based authentication**, **webhooks**, and **event-driven systems**. - Proven experience building reliable automation workflows with **observability**, **retries**, and failure handling. - Strong **JavaScript** and **Python** skills for backend logic, scripting, and internal tooling. - Solid **SQL** for data transformation, validation, and operational analytics (**Snowflake** a plus). - Advanced comfort with **JSON**, schemas, and data normalization for LLM and automation use cases. - Hands-on experience running **LLM-powered agents/automations** in production, including guardrails and output validation, plus prompt engineering frameworks. - Familiarity integrating with **CRM/support systems** (e.g., **Salesforce**, **Zendesk**). - An **A-player mindset**: bias for action, urgency, resilience through ambiguity, and strong ownership. ### Systems & Arc
Listing freshness
CronJobs last confirmed this listing 2h ago. If its source stops confirming the opening for seven days, this page is removed from active inventory.