AI Engineer

Overview

We are seeking a hands-on AI Engineer to join our newly formed AI Lab. In this role, you will work closely with our engineering and product teams to optimize and automate our software development lifecycle using AI tools. You will also help us leverage our unique data assets for business intelligence and future product development.

Key Responsibilities

• AI Code Integration: Collaborate with engineering teams to integrate AI-generated code (from tools like Claude and GitHub Copilot) into our production codebase of over 1.1 million lines.

• Workflow Optimization: Design, implement, and optimize processes for AI-assisted development, including prompt engineering, agent workflows, and automated testing.

• Tool Development: Develop and maintain tools to streamline the code review, testing, and deployment of AI-generated code.

• Architecture & Strategy: Work with stakeholders to define and document requirements for AI agents and current architecture practices.

• Data Pipeline Support: Support the creation of a data pipeline to enable business intelligence, analytics, and future AI/ML model training.

• Operational Monitoring: Explore and implement solutions for anomaly detection and real-time monitoring of operational data, such as access control logs.

• Mentorship: Stay current with the latest AI/ML and agent-based development practices to coach the team on new tools and best practices.

• Future Innovation: (Optional) Contribute to the development of proprietary models or data products leveraging our unique datasets.

Requirements

• Experience: 2+ years in AI/ML engineering, software engineering, or a related field.

• AI Proficiency: Hands-on experience with AI code generation tools (Claude, GitHub Copilot, OpenAI Codex) and integrating their output into large codebases.

• Technical Skills: Proficiency in at least one of the following: .NET (C#), React, React Native, or Python.

• Platform Knowledge: Experience with cloud platforms (preferably AWS) and familiarity with SaaS architectures.

• SDLC Mastery: A solid understanding of the software development lifecycle, QA, and automated testing.

• Collaboration: Strong communication skills with the ability to work effectively with distributed teams.

• Availability: Ability to work with partial overlap to US Eastern Time (until at least 2-3pm EST).

Desired Skills (Nice to Have)

• Experience with large-scale enterprise codebases.

• Familiarity with agent-based development, prompt engineering, and AI workflow optimization.

• Knowledge of data engineering, data pipelines, or business intelligence.

• Experience with anomaly detection, real-time data processing, or IoT data.

• Exposure to LLM fine-tuning or Retrieval-Augmented Generation (RAG).

• Domain knowledge in construction tech or workforce management.