Junior AI Engineer

Bigge Crane and Rigging•Houston, TX

13h

About The Position

Bigge Crane and Rigging is an AI-first company that has established a dedicated AI Engineering department to ensure its continued advancement. Employees work with frontier AI tools daily, and engineers build connections to integrate these tools into the company's core systems, including fleet, sales, scheduling, and documents. The company prioritizes building solutions tailored to its specific needs over relying solely on off-the-shelf software. This role offers the opportunity to work on real-world problems with a significant amount of operational data, and contributions are recognized by name.

Requirements

Bachelor’s degree in Computer Science, Engineering, Data Science, or equivalent experience.
1 to 3 years of professional experience, with shipped work you can show us: a deployed project, a production contribution, a working system you built. We screen on what you have built, not how long you have been employed.
Working proficiency in Python or TypeScript, and willingness to become proficient in both. You will use both.
Experience building against real APIs: authentication, error handling, and reading documentation that is sometimes wrong.
Hands-on experience with LLM APIs and prompt engineering, through work, coursework, or personal projects.
Strong communication and problem-solving abilities, with the willingness to work directly with field and office personnel.
Coachable, organized, and able to learn quickly in a fast-moving environment.
Have a current valid driver’s license along with a clean driving record.

Nice To Haves

Exposure to the Model Context Protocol or other tool-calling architectures.
Next.js, React, and Tailwind.
Docker and cloud deployment of any kind.
Local model serving or fine-tuning experiments, at any scale.
Prior work or internship in construction, heavy equipment, logistics, or industrial operations.

Responsibilities

Build and extend MCP connectors against Bigge systems of record, including WorkPro (Bigge’s internal asset management lifecycle platform), D365, and Microsoft 365, under established patterns and review.
Implement components of AI agents and agentic workflows designed with the Director of AI Engineering.
Write and maintain tests, evaluation sets, and regression checks for systems before they ship and after every change.
Integrate LLM capability into internal applications and APIs under direction.
Attend process discovery sessions with business units to observe workflow mapping and contribute to process documentation.
Assist in collecting performance baselines and metrics for departmental initiatives.
Adhere to responsible-AI practices, data governance standards, and IT security requirements.
Write clean, tested, documented code.
Participate in code review as author and grow into reviewing others.