Staff Operations AI Engineer

We need to output only HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections where posting has real specific content. Must not repeat job title. Must not include Job ID etc. Must remove boilerplate like EEO, etc. Must preserve all substantive info. We need to parse the posting. Content: - About Checkr (company description) – maybe part of About the role? The instruction: "About The Role" heading present. So we should have a section "About the role" containing the description after "About The Role". The earlier "About Checkr" is company overview; maybe we can include under "About the role"? The instruction says use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we should include only those headings if content exists. "About the role" definitely exists. We need to extract responsibilities: "What You’ll Do" bullet points. Responsibilities: list items under "What You’ll Do". Should be

• . Requirements: "What You Bring" includes required experience bullet points. Also "Systems & Architecture Track record..." and "Mindset & Leadership". Those could be part of Requirements or Qualifications. The instruction: we have separate headings for Requirements, Qualifications, Skills. We need to decide mapping. Usually Requirements = required experience; Qualifications = maybe education? Not present. Skills = specific technical skills. We can split. But we must not invent sections with filler. So we need to see if we have content for each. We have: - Required Experience bullet list (5-7+ years ...). That's requirements. - Systems & Architecture Track record bullet list (maybe also requirements or qualifications). Could be part of Requirements. - Mindset & Leadership bullet list (maybe also qualifications). - Nice-to-Have Experience bullet list (could be Qualifications or Skills). But we should only include sections if posting has real specific content. Nice-to-Have is specific content, so we could include under "Qualifications" or "Skills". However we have separate headings; we need to decide. We also have Pay Transparency Disclosure with salary ranges for Denver and Nashville. That's Pay. We have Benefits: list under "What We Offer". Also mention in-office work environment, hub locations, etc. That's benefits. Schedule: mention "Individuals are expected to work from the office 3+ days a week." That's schedule. Thus we have content for About the role, Responsibilities, Requirements, Qualifications (maybe Nice-to-Have), Skills (maybe required technical skills), Benefits, Pay, Schedule. We need to avoid filler like "commensurate with experience". Not present. We must not include boilerplate like EEO, Applicant Privacy Policy, etc. Remove those. We must preserve all substantive information; do not invent or summarize away detail. Thus we need to extract each bullet exactly as in posting, preserving wording. Let's extract sections. About the role: The paragraph after "About The Role" up to before "What You’ll Do". It includes: "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. 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." We should keep that as

  . Responsibilities: Under "What You’ll Do" there are subheadings: "AI Agent Integration & Automation Architecture", "Systems Engineering & Data Foundations", "AI Quality, Safety & Guardrails". Each has bullet points. We need to output a list of duties. Could combine all bullet points under one

  . Must preserve all detail. Let's extract bullet points: Under 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 and event-driven patterns, and robust automation workflows that coordinate actions across tools like Zendesk, Salesforce, and internal services. - Ensure AI-driven operations are resilient through strong error handling, retries, observability, and fallback mechanisms. - Proactively identify integration gaps, system bottlenecks, and failure modes, and lead the technical solutions that improve reliability and scale. Under Systems Engineering & Data Foundations: - Build and maintain the technical foundations that power 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 through documentation and diagrams, and serve as a technical authority across teams to ensure consistent, high-quality execution. Under AI Quality, Safety & Guardrails: - Implement guardrails, validation rules, and safety checks that ensure 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 in AI-driven decisions. We'll put all as
  • . Requirements: Under "What You Bring" there is "Required Experience" bullet list. Let's extract: - 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 expertise for backend logic, scripting, and internal tooling - Solid SQL experience 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 or automations in production, including guardrails and output validation, with proven experience in prompt engineering frameworks - Familiarity with integrating with CRM and support systems (e.g., Salesforce, Zendesk) - An A-player mindset with a strong bias for action: you raise the bar, move with urgency, stay resilient through ambiguity, and take ownership to deliver meaningful outcomes Also there is "Systems & Architecture" bullet list: - Track record designing end-to-end integration architectures across multiple platforms - Ability to translate complex operational needs into scalable, maintainable technical systems - Experience in anticipating API changes, schema drift, and downstream impacts in production environments And "Mindset & Leadership": - Systems thinker who understands how data, automation, and AI interact across the stack - Strong sense of ownership and commitment to building reliable, testable, observable systems - High bar for engineering rigor, with sound judgment around AI safety, governance, and compliance - Clear communicator who collaborates effectively across technical and non-technical partners - Role model of Checkr’s values; mentors others and contributes to a healthy, inclusive team culture These could be considered Requirements or Qualifications. We need to split into Requirements and Qualifications maybe. We have also "Nice-to-Have Experience": - Direct experience with Tray.io / Make / Zapier / UiPath - Programming experience in Python - Snowflake specifically (vs strong SQL generally) - Salesforce or Zendesk integrations - Front-end UI widgets / embeds - Prior work in operations technology specifically (vs platform, infra, or product engineering) These could be Qualifications or Skills. We also have specific skills mentioned in Required Experience: JavaScript, Python, SQL, API design, OAuth, webhooks, event-driven, JSON, schemas, LLM, prompt engineering, etc. Could be Skills. We need to decide mapping to avoid thin sections. Perhaps we can combine Required Experience + Systems & Architecture + Mindset & Leadership into Requirements (since they are all required). Nice-to-Have into Qualifications. Skills maybe we can extract from Required Experience (like JavaScript, Python, SQL, API design, etc.) but that may be redundant. But the instruction: "Prefer a few substantive sections over many thin ones." So we could have sections: About the role, Responsibilities, Requirements, Qualifications, Benefits, Pay, Schedule. Possibly omit Skills if covered elsewhere. We need to ensure we don't omit any substantive info. If we put Nice-to-Have under Qualifications, we keep it. If we put Required Experience etc under Requirements, we keep it. Skills maybe we can omit if we think it's covered; but we might lose explicit mention of JavaScript, Python, SQL, etc. However those are already in Required Experience bullet points, so they are preserved. So we can omit Skills section. Thus sections: - About the role - Responsibilities - Requirements - Qualifications - Benefits - Pay - Schedule Now we need to extract Benefits: Under "What We Offer" bullet list: - A fast-paced and collaborative environment - Learning and development allowance - Competitive cash and equity compensation, and opportunity for advancement - 100% medical, dental, and vision coverage - Up to $25K reimbursement for fertility, adoption, and parental planning services - Flexible PTO policy - Monthly wellness stipend Also after that: "At Checkr, we believe an in office work environment strengthens collaboration, drives innovation, and encourages connection. Our hub locations are Denver, CO; San Francisco, CA; Nashville, TN; and Santiago, Chile. Individuals are expected to work from the office 3+ days a week. In-office perks are provided, such as lunch five times a week, a commuter stipend, and an abundance of snacks and beverages. A relocation stipend may be available for those willing to relocate to a Checkr hub location." These are also benefits/perks. Should we include them under Benefits? Yes, they are substantive. We'll add them as additional
  • items. Pay: We have Pay Transparency Disclosure with salary ranges for Denver and Nashville. Also mention "On-target Earnings OR Base Salary range (Denver, CO) $150,000—$176,000 USD" and "(Nashville, TN) $136,000—$159,980 USD". Also earlier: "We use geographic cost of labor as an input to develop ranges for our roles and as such, each location where we hire may have a different range. If this role is remote, we have listed the top to the bottom of the possible range, but we will specify the target range for an exact location when you are selected for a recruiting discussion." That's substantive. We'll include that as

    maybe. Schedule: "Individuals are expected to work from the office 3+ days a week." Also maybe mention hub locations? But schedule is about work schedule. We'll include that as

    . Now we need to output HTML fragment with

    headings and

    or

    • . Ensure no extra text. Let's craft. First, About the role:

      About the role

      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. 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.

      Second, Responsibilities:

      Responsibilities

      • Design and own the integration architecture that enables AI Agents to operate safely and reliably across Checkr systems and third-party platforms.