AI & Automation Engineer
Comfort Systems USAAbout the role
Key Responsibilities
AI & Automation Development
Design, develop, and deploy AI-powered solutions (e.g., predictive analytics, document processing, intelligent assistants, computer vision where applicable).
Build and maintain automation workflows using tools such as RPA, low-code/no-code platforms, APIs, and custom scripts.
Develop models and systems that integrate with ERP, payroll, HRIS, project management, accounting, and field data systems.
Enterprise Enablement
Partner with individual operating companies to identify automation and AI opportunities aligned with their unique workflows.
Create reusable frameworks and templates that can be adapted across multiple operating companies.
Balance standardization with flexibility to support decentralized business units.
Data & Integration
Work with structured and unstructured data from multiple sources (financial systems, project data, contracts, invoices, timesheets, etc.).
Build and maintain secure data pipelines and integrations.
Ensure data quality, governance, and compliance across systems.
Strategy & Innovation
Identify high-impact use cases for AI and automation across construction operations, back-office functions, and shared services.
Stay current on emerging AI technologies and evaluate their applicability to the organization.
Contribute to the long-term AI and automation roadmap.
Documentation & Support
Document solutions, workflows, and best practices.
Train end users and provide ongoing support for deployed solutions.
Collaborate with IT, security, and business stakeholders to ensure stability and scalability.
Required Qualifications
Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field (or equivalent practical experience).
3–7+ years of experience in automation, AI, machine learning, or software engineering.
Hands-on experience with automation tools (RPA platforms, scripting, APIs, workflow tools).
Strong programming skills in Python, JavaScript, or similar languages.
Experience working with databases, data pipelines, and cloud platforms.
Ability to translate business problems into technical solutions.
Strong communication skills and comfort working with non-technical stakeholders.
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