Principal AI Engineer

The HOTH•St. Petersburg, FL

1d•$180,000 - $200,000•Hybrid

About The Position

We're looking for a Principal AI Engineer to help build the future of NextNet AI. This isn't a management role, and you won't spend your days sitting in status meetings or managing people. This is a role for someone who loves building. You'll partner directly with our CTO to solve the hardest technical problems across our platform. We're looking for someone who can jump into unfamiliar systems, understand them quickly, and ship production-quality solutions with confidence. Some days you'll be debugging a frontend issue that turns into a backend API problem. Other days you'll be optimizing AI pipelines, designing scalable cloud infrastructure, improving distributed services, or shipping entirely new product capabilities. If you're the engineer people call when nobody else can figure something out, keep reading! Please note: This is a senior, hands-on engineering position. While you'll partner closely with technical leadership, this role does not include people management responsibilities.

Requirements

10+ years building production software.
Have built production AI applications that real customers use.
Can comfortably move between frontend, backend, cloud infrastructure, and AI systems.
Strong Python experience.
Hands-on AWS experience.
Enjoy debugging difficult technical problems.
Prefer shipping software over talking about software.
Take ownership without needing a lot of direction.
Care deeply about writing maintainable, scalable systems.

Nice To Haves

Experience with distributed systems.
Experience with Terraform or Infrastructure as Code.
Experience with LLMs, RAG, vector databases, or agentic workflows.
Experience scaling SaaS products.
Experience in SEO, digital marketing, or MarTech.

Responsibilities

Build and deploy production-grade AI software.
Own complex engineering initiatives from design through deployment.
Work comfortably across frontend, backend, infrastructure, cloud, and AI systems.
Design scalable backend services and APIs.
Improve platform performance, reliability, and observability.
Debug issues across distributed systems and identify root causes rather than surface symptoms.
Reduce technical debt and improve long-term maintainability.
Evaluate emerging AI technologies and recommend practical adoption.
Document technical decisions that help the team move faster.
Partner directly with the CTO on architecture, platform evolution, and strategic technical initiatives.