Job Purpose
The Software Engineer will design, develop, and implement software applications that support and enhance industrial automation systems. This role will collaborate closely with multidisciplinary engineering teams to deliver scalable, reliable, and high‑performance automation solutions that enable operational efficiency across reverse logistics environments.
Primary Responsibilities
(Percentages reflect approximate time allocation and total 100%.)
Software Development – 60%
- Design, develop, implement, debug, and document new and existing software applications for industrial automation systems.
- Integrate specialized automation technologies including machine vision, data processing, and machine learning.
- Develop reporting, visualization, and data‑driven tools to support operational decision-making.
- Build scalable and reliable deployable libraries and tools to support reverse logistics operations.
Technical Leadership – 10%
- Provide guidance on software engineering best practices and architecture.
- Participate in code reviews and ensure adherence to development standards.
- Solve complex technical challenges and support continuous improvement initiatives.
Requirements Analysis & Collaboration – 10%
- Partner with project managers, automation engineers, and cross‑functional stakeholders to translate business and technical requirements into clear specifications.
- Support scoping, planning, and prioritization of automation projects.
Research & Development – 20%
- Evaluate emerging technologies, frameworks, and tools relevant to industrial automation.
- Develop prototypes and proof‑of‑concepts to expand the team’s technical capabilities and internal tool library.
Required Experience, Skills & Knowledge
Education
- Bachelor’s degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience.
Experience
- 5+ years of professional software development experience.
- Demonstrated experience designing and implementing scalable, robust solutions for industrial automation environments.
Technical Skills
- Expertise architecting and developing complex software systems and selecting appropriate technologies.
- Strong proficiency in programming languages such as C++, Python, and C#, with solid understanding of software engineering principles.
- Experience designing and integrating RESTful and/or GraphQL APIs.
- Familiarity with machine vision technologies, including tools like OpenCV and hardware integration.
- Experience developing or integrating machine learning models for real‑time industrial applications (TensorFlow, PyTorch a plus).
- Knowledge of DevOps practices, CI/CD pipelines, and automated testing.
- Experience with SQL and NoSQL databases, data modeling, and performance optimization.
- Experience working with large datasets, real‑time data streaming, and data visualization tools.
- Experience with cloud platforms (AWS, Azure, or Google Cloud) and cloud‑native architectures.
- Understanding of microservices and container technologies such as Docker and Kubernetes.
Leadership & Soft Skills
- Excellent written and verbal communication skills, with the ability to explain complex concepts to diverse stakeholders.
- Strong analytical and problem‑solving abilities to handle challenging real‑time automation scenarios.
- Proven ability to collaborate effectively in large, global, cross‑functional teams.
Preferred Qualifications
(These are beneficial but not required.)
- Master’s degree in Computer Science, Computer Engineering, or related technical field.
- Knowledge of industrial communication protocols (e.g., Modbus, OPC-UA, EtherCAT).
- Experience integrating with PLCs, SCADA, and HMI systems.