Cayuse
AI Solution Engineer
engineeringfull-timeRemote
SALARY
Not listed
WORK TYPE
remote
JOB TYPE
full-time
INDUSTRY
general
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About the role
Responsibilities
As an AI Solution Engineer, you will work across teams to surface, design, and deliver AI-driven improvements. Your focus will be on business impact, solution quality, and enabling others to build confidently with AI.
- Efficiency Discovery & Opportunity Mapping: Conduct structured assessments across business units to identify manual, repetitive, or data-intensive workflows where AI can deliver measurable time and cost savings. Translate operational pain points into prioritized opportunity backlogs with clear ROI framing.
- AI Solution Design & Prototyping: Architect and build AI-powered solutions — including LLM integrations, intelligent automation, and ML-assisted workflows — from concept through production. Develop rapid prototypes to validate feasibility and demonstrate value before full-scale investment.
- Cross-Functional Stakeholder Partnership: Act as the technical bridge between business stakeholders, product management, and engineering teams. Translate ambiguous business requirements into concrete AI solution designs and communicate tradeoffs clearly to both technical and non-technical audiences.
- Implementation & Delivery: Own end-to-end delivery of AI solutions, including integration with existing systems, API design, prompt engineering, evaluation frameworks, and monitoring. Ensure solutions meet reliability, security, and scalability standards.
- AI Enablement & Internal Capability Building: Develop internal tooling, documentation, and training to help non-technical teams adopt AI tools effectively. Champion AI literacy across the organization and establish best practices for responsible, effective AI use.
- AI Governance & Responsible Deployment: Define and enforce standards for responsible AI deployment, including data privacy, bias mitigation, auditability, and compliance. Ensure all solutions align with organizational and regulatory requirements.
Qualifications
Core Experience
- 5+ years of professional experience in software engineering, data science, or a related technical discipline with a track record of delivering production-grade AI or automation solutions.
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