Automation Engineer (AI Systems)

About Us

Headquartered in Dallas, Texas,

**Divcon**

delivers fully integrated automation solutions

nationwide

that optimize performance, energy efficiency, and reliability across HVAC, lighting, power monitoring, and mission-critical systems. Leveraging advanced technologies - including Allen-Bradley PLCs, Ignition SCADA, and Delta DDC systems - we combine deep technical expertise with field-tested execution to deliver precise, scalable, and high-performance solutions.

About The Role

The

Automation Engineer

is responsible for identifying, designing, and deploying intelligent automation systems that eliminate manual processes across the organization.

This role transforms repetitive business workflows into scalable, AI-driven systems using modern orchestration platforms such as n8n, LangChain, and API-connected services.

You will work closely with software developers, engineers, project managers, finance, and operations to engineer reliable automation pipelines that improve accuracy, speed, and operational leverage.

This is a hands-on engineering role focused on implementation—not research or experimentation.

Key Responsibilities

**Identify**

**and Prioritize**

**Automation Opportunities**

• Audit internal workflows to identify manual, repetitive, or error-prone tasks
• Quantify time savings and operational impact of automation initiatives
• Prioritize automation projects based on measurable ROI
• Conduct discovery sessions with department leaders to surface impactful use cases
• In conjunction with executive leadership, architect automation roadmap aligned with strategic priorities

**Develop \& Deploy AI-Driven Automation**

• Build workflow orchestration pipelines using n8n
• Design and implement agent-based systems using LangChain or similar frameworks
• Develop LLM-powered solutions including structured output pipelines, RAG, tool-calling agents, and document automation
• Integrate across company systems (CRM, ERP, ticketing, telemetry platforms, internal tools)

**Engineer Reliable Systems**

• Design automation with proper logging, validation, and error handling
• Implement safeguards around data security and access control
• Develop reusable automation templates and internal standards
• Maintain organized repositories including version control, documentation, and release notes

**Collaborate**

**Cross-functionally**

• Partner with other teams, especially engineering and Software Developers to productionize scalable solutions when needed
• Participate in design reviews and architecture discussions
• Ensure automation systems align with internal development standards
• Liaise effectively across functions to ensure stakeholder buy-in and oversee change management

**Support \& Continuous Improvement**

• Monitor automation performance and reliability
• Troubleshoot integration failures and workflow gaps
• Iterate on deployed agents to improve accuracy and efficiency

Qualifications

• 5\+ years in automation engineering, systems integration, or software development, with principal focus on integration of artificial intelligence systems in business processes
• Hands-on experience with workflow orchestration platforms (n8n, Zapier, Make, or similar)
• Experience integrating REST APIs and external services
• Experience working with LLM platforms and agent orchestration frameworks
• Strong understanding of API authentication, JSON data transformation, workflow branching, logging, and observability
• Ability to move from concept to working deployment quickly
• Skilled at translating business requirements into technical solutions and communicating effectively with non-technical stakeholders

Preferred Qualifications

• Experience building RAG pipelines and vector database integrations
• Familiarity with structured prompting and output validation techniques
• Experience working alongside engineering teams in production environments
• Familiarity with Docker, cloud deployment, or CI/CD pipelines
• Experience in industrial, automation, or mission-critical environments

What Success Looks Like

• Manual workflows replaced with reliable automated systems
• Measurable reduction in labor hours across departments
• AI agents deployed into daily operational processes
• Clean, maintainable automation architecture adopted company-wide
• Clear documentation and repeatable automation standards established