<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, Amazon, 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><p>Join the IT Engineering team as a Staff AI Solutions Engineer, where you will serve as the primary driver of AI enablement and solutions engineering across all departments at Checkr. This is a highly visible, hands-on role that blends deep technical expertise with a passion for teaching and empowering others. You will lead the charge on understanding team-specific requirements, configuring and evaluating AI tools, building bespoke AI-powered solutions, and standing up templatizable workflows that scale across the organization. From running office hours and hackathons to creating reusable resources and training materials, you will be the go-to person for helping every team at Checkr unlock the full potential of AI.</p> <p><strong>What you’ll do: </strong></p> <ul> <li><strong>Requirements Gathering & Enablement:</strong> Embed with internal teams across departments to deeply understand their workflows, gather requirements, identify high-impact AI use cases, and translate business needs into actionable technical solutions.</li> <li><strong>Lead Office Hours & Hackathons: </strong>Own and facilitate recurring AI office hours for drop-in support and guidance. Design and lead company-wide AI hackathons that inspire experimentation, knowledge sharing, and the discovery of innovative use cases.</li> <li><strong>AI Tool Configuration & Evaluation:</strong> Evaluate, configure, and recommend the right AI tools and platforms for the organization. Stay on top of the rapidly evolving AI tooling landscape and make informed build-vs-buy recommendations.</li> <li><strong>Build Bespoke AI Solutions:</strong> Design, develop, and deploy custom AI solutions tailored to specific team needs—leveraging LLMs, RAG architectures, agentic workflows, and automation frameworks to solve real business problems.</li> <li><strong>Create Resources & Artifacts:</strong> Develop reusable playbooks, prompt libraries, workflow templates, how-to guides, and reference architectures that enable teams to self-serve on AI adoption.</li> <li><strong>Templatize AI Workflows:</strong> Architect and implement standardized, templatizable AI workflows that can be adapted and deployed across multiple teams and use cases, driving consistency and scale.</li> <li><strong>Training & Teaching:</strong> Lead hands-on training sessions, workshops, and demos to teach teams how to effectively use AI tools and integrate them into their day-to-day work. Act as a force multiplier by building AI fluency organization-wide.</li> <li><strong>Cross-Functional Collaboration:</strong> Partner closely with Engineers, Business Systems, Security, Data Engineering, and other AI Solutions Engineers to integrate AI technologies into existing systems, ensuring security, compliance, and scalability.</li> <li><strong>Strategic Planning & Roadmapping:</strong> Contribute to the AI strategy and roadmap at the organizational level, aligning initiatives with business priorities and ensuring AI investments deliver maximum value.</li> <li><strong>Communicate & Evangelize: </strong>Present findings, demo solutions, share progress updates, and advocate for AI adoption with stakeholders ranging from individual contributors to executive leadership.</li> </ul> <p><strong>What you’ll bring: </strong></p> <ul> <li>Bachelor’s degree in Computer Science or equivalent experience. A graduate degree is a plus.</li> <li>5+ years of experience in engineering, solutions engineering, or technical enablement roles, with a track record of deploying solutions that measurably enhance productivity.</li> <li>3+ years of hands-on experience developing AI
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