Full-time
Technical Automation & Software Engineering Lead
Posted on 05 March 26 by Brenden Cotter
- Grand Rapids, Michigan
- $ - $
Powered by Tracker
Job Description
Description: An innovative organization in West Michigan is seeking a technical leader to design and support advanced automation and software solutions that integrate industrial controls, machine vision, modern application development, and containerized deployments. This role will lead a team supporting smart manufacturing and automation initiatives, building scalable applications and vision systems used in operational environments.
Responsibilities/skills:
Required Qualifications:
Preferred Qualifications:
#IND1
Responsibilities/skills:
- Lead and mentor a team of automation engineers and software developers.
- Design and develop machine vision and automation-focused applications.
- Build and maintain scalable APIs and backend services.
- Support containerized deployments for edge and on-premise systems.
- Participate in the full software development lifecycle, including design, development, testing, deployment, and support.
- Write and maintain unit, integration, and system tests.
- Collaborate within an Agile development environment.
- Troubleshoot and resolve issues across applications, systems, and infrastructure.
Required Qualifications:
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
- Experience with modern programming languages such as Python, TypeScript, or C#.
- Experience with modern front-end frameworks (React, Angular, or similar).
- Familiarity with containerization technologies and orchestration platforms.
- Experience with relational databases.
- Familiarity with REST APIs, CI/CD pipelines, and distributed application architectures.
- Strong problem-solving and communication skills.
- Ability to quickly learn and adapt to new technologies.
Preferred Qualifications:
- Experience working with industrial automation or PLC-based environments.
- Exposure to computer vision frameworks or machine learning models.
- Experience working in manufacturing, logistics, or industrial environments.
- Familiarity with observability and monitoring tools.
- Experience with messaging systems or event-driven architectures.
#IND1