Forward Deployed AI Engineer II

Location: New York

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences.

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless  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 product ionize 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

How you’ll measure success:

Number of high-impact internal and customer-facing AI use cases launched

Adoption and measurable business impact of AI-powered tools and features

Quality, reliability, latency, and safety of deployed AI systems

Reduction in manual work, operational cost, or customer support volume

Improvement in customer experience, containment, accuracy, or workflow efficiency

Percentage of AI use cases with clear owners, evals, monitoring, and governance controls

Speed from AI opportunity identification to prototype, pilot, and production launch

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…