Staff AI Solutions Engineer

Responsibilities

• Gather requirements from internal teams, identify high-impact AI use cases, and translate business needs into technical solutions.
• Lead recurring AI office hours and company-wide AI hackathons.
• Evaluate, configure, and recommend AI tools and platforms, including build-versus-buy decisions.
• Design, develop, and deploy custom AI solutions using LLMs, RAG architectures, agentic workflows, and automation frameworks.
• Create reusable playbooks, prompt libraries, workflow templates, how-to guides, and reference architectures.
• Architect standardized, templatizable AI workflows for deployment across teams and use cases.
• Lead hands-on training sessions, workshops, and demonstrations to improve organization-wide AI fluency.
• Collaborate with Engineering, Business Systems, Security, Data Engineering, and other AI Solutions Engineers to integrate AI technologies securely and scalably.
• Contribute to organizational AI strategy and roadmaps.
• Present findings, demonstrate solutions, communicate progress, and advocate for AI adoption with stakeholders from individual contributors through executive leadership.

Requirements

• Bachelor’s degree in Computer Science or equivalent experience; a graduate degree is a plus.
• 5+ years of experience in engineering, solutions engineering, or technical enablement roles, with a record of deploying productivity-enhancing solutions.
• 3+ years of hands-on experience developing AI-centric products and solutions, including machine learning, generative AI, LLMs, RAG architectures, agentic frameworks, and prompt engineering.
• Deep proficiency in Python and experience with AI frameworks and integrating LLM models into applications.
• Familiarity with AWS, Google Cloud, or Azure.
• Experience leading enablement programs, including office hours, hackathons, training sessions, and scalable documentation.
• Experience gathering requirements from non-technical stakeholders and translating them into well-scoped technical solutions.
• Ability to solve open-ended problems in unstructured environments and turn complex information into actionable plans.
• Strong communication and presentation skills, with the ability to explain complex AI concepts to technical and executive audiences.
• Ability to architect solutions, write production code, create training materials, and facilitate workshops.
• Passion for AI and helping others use it effectively.

Compensation and Benefits

• On-target earnings or base salary: $177,000–$208,000 USD for San Francisco, CA.
• Learning and development allowance.
• Competitive cash and equity compensation with advancement opportunities.
• 100% medical, dental, and vision coverage.
• Up to $25,000 reimbursement for fertility, adoption, and parental planning services.
• Flexible PTO policy.
• Monthly wellness stipend.
• In-office perks including meals, commuter stipend, snacks, and beverages.
• Relocation stipend may be available for relocation to a Checkr hub location.