Forward Deployed AI Engineer II

About the Role

In this role, you will design, build, and deploy AI-powered systems that accelerate AI adoption across CLEAR’s internal workflows and customer-facing product experiences.

This role will partner directly with Product, Engineering, Data, Security, Legal, Compliance, Operations, and business teams to identify high-impact AI opportunities, rapidly prototype solutions, and productionize reliable, secure, and measurable AI systems. You will own use cases end-to-end, from discovery and evaluation through launch, monitoring, and iteration.

What You'll Do

• Discover, prioritize, and build AI use cases across internal tools, employee workflows, and customer-facing product features
• Partner with Product, Engineering, Data, Security, Legal, Compliance, and Operations to translate business needs into AI-driven solutions
• Rapidly prototype AI agents, LLM applications, RAG workflows, automation tools, and product experiences
• Productionize validated AI use cases with strong evaluation, monitoring, logging, fallback paths, and operational ownership
• Build reusable patterns for prompt management, retrieval, tool use, evals, guardrails, and human-in-the-loop workflows
• Implement responsible AI best practices, including privacy, security, model governance, risk review, and customer impact assessment
• Measure and communicate AI impact across adoption, quality, cost reduction, productivity, customer experience, and business outcomes

What You’re Great At

• 2+ years of experience in software engineering, AI engineering, machine learning engineering, data engineering, or related technical roles
• Hands-on experience building with LLMs, AI agents, RAG, model APIs, prompt engineering, or AI application frameworks
• Strong programming skills in Python and/or another modern backend language
• Experience building and deploying production systems with APIs, data platforms, cloud infrastructure, logging, monitoring, and testing
• Ability to work directly with business teams to understand ambiguous workflows and turn them into usable AI products
• Strong product judgment and ability to identify practical, high-ROI AI use cases
• Understanding of responsible AI concepts, including evals, guardrails, data privacy, security, human oversight, and model governance
• Ability to communicate complex technical concepts to technical, non-technical, and executive stakeholders
• Comfort operating in fast-paced, ambiguous environments with strong ownership from idea to impact
• Passion for building AI systems that are practical, secure, measurable, and user-centric