Backend Engineer, Logistics Forecasting & Simulations

Rune Technologies; Honolulu (HI); On-site; USD 190,000 - 210,000; Full time

Benefits offered by this job

Comprehensive benefits

401(k) plan

Equity

Job summary

Rune Technologies in the United States is seeking a Backend Software Engineer focused on simulations for TyrOS. You will own production-grade simulation and forecasting software, collaborating with a forecaster lead and platform team to model logistics outcomes in complex operational environments.

The ideal candidate has 4+ years in software engineering and is fluent in Python, C++, or Go, with a strong foundation in production-quality engineering and a math or science background.

Qualifications

• 4+ years of software engineering experience in scientifically or mathematically complex domains.
• Ability to reason about correctness using physics or math, not just software behavior.
• Proficiency in Python, C++, or Go.
• Strong production-quality software engineering foundation.
• Math or science background through degree, graduate work, or professional experience.
• Strong ownership and bias for action.

Responsibilities

• Build and own production-grade simulation and forecasting software, focusing on Rune's logistics forecaster.
• Work with mathematical models, numerical methods, and formulas to implement software grounded in physics or math.
• Collaborate with forecaster lead and platform team to integrate simulation into TyrOS workflows.
• Participate in design discussions and code reviews to enforce engineering rigor.
• Triage and debug production issues ensuring reliability and fast iteration.
• Collaborate with engineers, product managers, and military stakeholders to meet real-world sustainment requirements.

Skills

Python

C++

Go

Education

Science/Engineering degree

Tools

AWS

Kubernetes

Job description

Rune Technologies in the United States is seeking a Backend Software Engineer focused on simulations for TyrOS. You will own production-grade simulation and forecasting software, collaborating with a forecaster lead and platform team to model logistics outcomes in complex operational environments.

The ideal candidate has 4+ years in software engineering and is fluent in Python, C++, or Go, with a strong foundation in production-quality engineering and a math or science background.