Forward Deployed AI Engineer I
CLEAR
This job at a glance
- Who can apply
- New grads and up to 2 years
- Must know
- OperationsLLMsMachine learningREST APIsPythonStakeholder management
- Work
- On-site in New York
- Pay
- Not stated by the employer.
- Skill demand
- LLMs56%REST APIs45%Machine learning43%Operations30%of 99 similar entry-level jobs posted in the US this week
- Listed
- Oct 29, 2026 · still open
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About the Role
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.
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.
Key Responsibilities
- 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
Requirements & Tech Stack
- 0-2 years of experience in software engineering, AI engineering, machine learning engineering, data engineering, or related technical roles
- Some 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
- Some 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
- Good product judgment and ability to identify practical, high-ROI AI use cases
- Knowledge 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