The Role:
As a Senior Software Engineer for GM International Operations (GMIO) Regional Supply Chain Execution, you will design, build, and operate end‑to‑end web applications and services across the stack, leveraging Powerbuilder, Java, Springboot on the backend and modern front‑end frameworks (such as Angular, React) on the client. You’ll work collaborate closely with cross-functional teams and stakeholders as needed to implement capabilities as required. You'll also implement scalable solutions while ensuring robust quality through automated testing, CI/CD, and comprehensive observability in Pure Agile.
What You Will Do:
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End-to-End Development: Take ownership of the software development lifecycle—from design and coding to testing and deployment—for critical features and components within our enterprise applications.
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Technical Leadership & Mentorship: Provide technical guidance and mentorship to fellow developers, fostering a culture of
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excellence by sharing best practices, conducting constructive code reviews, and supporting team growth.
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Strategic Contribution: Act as a key technical advisor during portfolio planning, providing accurate effort estimations and ensuring development initiatives are aligned with long-term strategic objectives.
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Champion Quality & Automation: Uphold the highest standards of code quality and system reliability by authoring comprehensive automated tests and advancing our CI/CD pipelines to enable robust continuous delivery.
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Ensure Operational Excellence: Proactively support the deployment, monitoring, troubleshooting, and optimization of applications in various environments, utilizing modern DevOps tools and practices to ensure stability and performance.
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We are looking for a seasoned senior software engineer who can architect, build, and lead the development of robust enterprise solutions. The ideal candidate will have a proven track record in full-stack development and a passion for mentoring teams.
Your Skills & Abilities (Required Qualifications):
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Bachelor’s degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience.
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Minimum of 5 years of experience designing and developing enterprise-scale applications.
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Technical Architecture: Deep experience with modern architectures including microservices, micro-frontends, and cloud-native development on platforms like AWS, Azure, or Google Cloud.
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Powerbuilder and Client Server technologies including Powerbuilder, Pro*C, ODBC, DataWindow design, PowerBuilder IDE
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Full-Stack Proficiency: Front-End: Advanced skills in HTML, CSS, JavaScript, TypeScript, and modern frameworks such as Angular or React.
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Full Stack Proficiency: Back-End: Expertise in Java and frameworks like Spring Boot, Spring MVC, or Quarkus.○
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DevOps & Infrastructure: Hands-on experience with containerization (Docker) and orchestration (Kubernetes), including deployment in OpenShift environments.
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Proficiency in implementing and managing CI/CD pipelines with tools like Jenkins,
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Azure DevOps, or GitHub Actions.
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Data Management: Strong proficiency with relational databases such as Oracle, PostgreSQL, and/or SQL Server.
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Demonstrated experience in and mentoring development teams.
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A strong commitment to software quality with a background in developing comprehensive automated tests.
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Soft Skills: Excellent problem-solving, communication, and collaboration skills, with a passion for continuous learning and adopting new technologies.
What Will Give You A Competitive Edge (Preferred Qualifications):
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Domain Knowledge: Familiarity or experience within the Supply Chain business domain.
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Bilingual: Preference given to those proficient in English as well as Korean
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Modern Ops: Proficiency with Infrastructure as Code (IaC) tools such as Terraform or Bicep.
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AI-Augmented Development: Practical experience using AI-powered tools like GitHub Copilot or Azure AI Studio to enhance productivity, code quality, and innovation.
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Applied AI/ML: Hands-on experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Hugging Face) and applying ML/NLP models to real-world enterprise problems like predictive analytics or intelligent automation.
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Experience deploying solutions on cloud ML platforms (e.g., Azure ML, AWS SageMaker, GCP Vertex AI) is a significant plus.
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