Artificial Intelligence Engineer

My client is seeking an Applied AI Platform Engineer to lead the development, deployment, and long-term ownership of the firm’s internal AI ecosystem. This is not a research-focused AI role or a position centered on experimentation and prototyping. Instead, the ideal candidate will be a strong software engineer who has evolved into AI, bringing a deep background in backend development, platform engineering, infrastructure, or DevOps.

This individual will be responsible for building and maintaining production-grade AI solutions that support traders, researchers, and operational teams. Success in this role requires someone who can own the entire lifecycle of AI products, from architecture and development through deployment, monitoring, support, and continuous improvement. The person should be comfortable operating as both the AI expert and the backend/platform engineer behind the solution.

This role will partner closely with a dedicated Forward Deployed Engineer (FDE) who serves as the bridge between business users and the engineering team. The FDE will work directly with traders, researchers, and operations teams to identify opportunities for AI-driven solutions, gather requirements, and drive adoption. The Applied AI Engineer will be responsible for architecting, building, deploying, and supporting the underlying systems and applications that bring those ideas to life. Together, they will own the end-to-end delivery of Trillium’s internal AI initiatives.

• 5+ years of software engineering experience with a background in Backend Engineering, Platform Engineering, Infrastructure Engineering, or DevOps.
• Hands-on experience building and deploying AI-powered applications utilizing LLMs.
• Strong Python development experience.
• Experience developing backend services, APIs, distributed systems, and production applications.
• Experience with OpenAI, Anthropic, LangChain, LangGraph, or similar AI technologies.
• Experience deploying and supporting applications within AWS, Azure, or GCP environments.
• Strong knowledge of Kubernetes, Docker, CI/CD pipelines, monitoring, and cloud infrastructure.
• Experience owning applications throughout their full production lifecycle.
• Strong understanding of software architecture, system design, and platform operations.
• Ability to work independently and take complete ownership of projects

PLUSSES:

• Bachelor’s degree in a technical, analytical, or creative field