Software Engineer II- AI Solutions

Doosan CorpMinneapolis, MN
20h

About The Position

The Software Engineer II is responsible for designing, developing, and optimizing scalable, reliable full-stack solutions that incorporate AI, data-driven features, and modern architectural principles. This role involves working independently on core features, collaborating across teams, and contributing to architectural decisions, system performance, and operational improvements. The role supports ongoing organizational growth, including activities such as AI lifecycle management, product support, and quality assurance. 

Requirements

  • Bachelor's degree in Computer Science, Software Engineering, or a related field.
  • 2-5 years of proven experience with software development, design, and deployment.
  • Strong proficiency in multiple programming languages (Java, Python, NodeJS) and at least one modern frontend framework (e.g., React, Angular, or Vue) and experience with cloud platforms (AWS, Azure, GCP) and Infrastructure as Code (IaC).
  • Deep understanding of multiple software patterns such as microservices, APIs, AI Agents, or data pipelines.
  • Demonstrated ability to independently troubleshoot complex system issues and provide effective solutions across the full stack.
  • Excellent communication skills with the ability to articulate technical concepts across teams and stakeholder groups.
  • Effective collaboration skills, with experience working with cross-functional teams in Agile environments.
  • Problem-solving skills with a track record of addressing systemic issues, optimizing performance, and driving best practices.
  • < 10% travel

Responsibilities

  • Design and develop scalable, reliable full-stack solutions, including APIs, AI Agents, data engineering pipelines, and intuitive user interfaces, adhering to current architectural standards and best practices.
  • Ensure solutions are secure, scalable, maintainable, and follow responsible AI guidelines.
  • Write comprehensive unit, integration, and automation tests to ensure high quality and reduce defects throughout the application stack.
  • Document technical designs, architecture decisions, and operational procedures clearly for team and operational use.
  • Troubleshoot and resolve complex operational issues, performance bottlenecks, and deployment problems proactively across the full stack.
  • Collaborate effectively with cross-functional teams—including product managers, data scientists, and infrastructure engineers—to translate requirements into technical solutions.
  • Contribute to code reviews and architectural discussions, evaluate new tools, and participate in continuous improvement initiatives.
  • Advocate for best practices in coding, security, and data privacy, and challenge ideas constructively to improve system robustness.
  • Support AI model lifecycle activities, software testing, and ongoing maintenance tasks to improve product quality and reliability.
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