Software Engineer – Scientific Computing, AI

BPCS, Comprehensive marketing solutions, ltd.

Software Engineer developing software solutions for scientific computing, machine learning, and simulation workloads. Collaborating with teams to enhance AI-powered tools and best practices in engineering.

Posted 6/30/2026full-timeRemote • Washington • 🇺🇸 United StatesJunior💰 $32 - $35 per hourWebsite

Tech Stack

Tools & technologies

SDLC

About the role

Key responsibilities & impact

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

What you’ll need

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.

Benefits

Comp & perks

Medical, dental, and vision coverage
Flexible Spending Account
401k program
Competitive PTO offerings
Parental Leave
Opportunities for professional growth and development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Software DevelopmentScientific ComputingData Science ApplicationsAutomation WorkflowsSimulation-Based ProjectsSoftware Development Lifecycle (SDLC)Coding StandardsTestingTroubleshootingAPIs

Soft Skills

Effective CommunicationCollaborationCustomer EngagementTechnical GuidanceVerbal and Written Communication

Certifications

Bachelor's Degree in Computer ScienceBachelor's Degree in Software Engineering