Software Engineer – Scientific Computing & AI

Blueprint is a technology solutions firm headquartered in Bellevue, Washington, that focuses on solving complex problems through innovative technology. As a Software Engineer, you will develop and enhance software solutions for scientific computing and AI, collaborating with customers and cross-functional teams to drive successful outcomes.

Responsibilities:

• Collaborate with product and engineering teams to support customer onboarding and technical adoption
• Develop, maintain, and own customer-facing GitHub repositories and related codebases
• Design, build, test, and deploy software solutions for scientific computing and data science applications
• Apply software engineering principles to address scientific, research, and computational challenges
• Create, maintain, and improve reusable AI agents, automation workflows, and community assets
• Utilize AI, LLMs, and agent-based technologies to enhance customer solutions and development processes
• Support machine learning and data science workflows through software development and integration efforts
• Contribute to simulation-based projects and computational science initiatives
• Troubleshoot technical issues, identify root causes, and implement effective solutions
• Follow software development best practices, including version control, testing, documentation, and code reviews
• Engage with customers to understand requirements, provide technical guidance, and drive successful outcomes
• Help establish and promote engineering best practices across customer and community projects

Requirements:

• Bachelor's degree in Computer Science, Software Engineering, or a related technical field
• 1–2+ years of professional experience in software engineering or software development
• 1–2+ years of experience using GitHub and version control systems in collaborative development environments
• 1–2+ years of experience or demonstrated familiarity with AI/LLM technologies, machine learning concepts, APIs, and Model Context Protocol (MCP) concepts
• Experience applying software engineering practices to scientific, research, computational, or data-driven applications
• Understanding of software development lifecycle (SDLC) principles, coding standards, testing, and source control
• Strong programming and problem-solving skills
• Ability to communicate technical concepts effectively with customers and cross-functional teams
• Experience troubleshooting software issues and implementing solutions
• Strong verbal and written communication skills
• Experience with scientific computing, computational science, or simulation-based applications
• Exposure to machine learning workflows, model development, or data science projects
• Familiarity with agentic AI systems and AI-driven automation
• Experience building or maintaining customer-facing open-source or GitHub-based projects
• Demonstrated ability to apply software development skills to scientific or research-oriented problems
• Experience creating reusable tools, agents, frameworks, or community assets
• GitHub portfolio showcasing relevant software development projects
• Knowledge of best practices for open-source development, collaboration, and repository management
• Experience supporting technical customers or working in customer-facing engineering roles