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# AI Engineer

- **Company:** Cantor Fitzgerald
- **Location:** United States
- **Experience:** Experienced
- **Salary:** $300,000.0 - $350,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Automation of Tests, C++ (Programming Language), Cloud Computing, Computer Programming, Python (Programming Language), Machine Learning, Software Construction, Software Engineering, Large Language Models, Prompt Engineering, AI Platforms, Information Technology, Production Code, Data Pipelines, Microservices
- **Published:** July 17, 2026
- **Apply:** https://www.dice.com/job-detail/85a593b6-2226-4309-874b-341c68d17f50

## About the Role

* Bachelor's degree in computer science, machine learning, or a related technical field.
 * 5+ years of professional software engineering experience, including production systems.
 * 2+ years of hands-on experience developing AI or LLM-powered applications.
 * Demonstrated experience building agentic AI systems, including tool-using agents and multi-step workflows.
 * Strong programming skills in C++ and Python, with a focus on writing production-quality code.
 * Experience with modern LLM development patterns, such as prompt engineering and structured outputs.
 * Practical understanding of LLM failure modes and mitigation strategies.
 * Experience designing evaluation frameworks for AI applications, including test datasets and scoring methods.
 * Hands-on experience with APIs, microservices, and cloud deployment.
 * Strong understanding of security, privacy, and responsible AI considerations.

## Description

* Design, build, and maintain production-grade AI applications for FMX's exchange business.
 * Develop agentic AI workflows utilizing LLMs, tool use, planning, and structured outputs.
 * Architect reliable AI application patterns with human-in-the-loop controls and monitoring.
 * Evaluate LLM-powered systems using quantitative and qualitative methods, including benchmark design and red-team testing.
 * Analyze model behavior, identify failure modes, and implement improvements for accuracy and reliability.
 * Build and integrate APIs, data pipelines, and vector databases to support AI application development.
 * Apply software engineering best practices, including clean architecture and automated testing.
 * Partner with cross-functional teams to translate business needs into technical designs.
 * Contribute to technical strategy and architectural decisions for AI platforms and reusable components.
 * Mentor other engineers and help raise the team's AI engineering capabilities.


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