Barr Geospatial Solutions (BGS) is expanding its Pipeline Intelligence Suite to convert complex geospatial data into predictive, real-time insight, aiming to redefine how energy infrastructure is monitored, analyzed, and protected.
Requirements
- Deep expertise in integrated systems, data, and software development — ideally across imagery, LiDAR, or remote-sensing applications.
- 5–10 years of experience in software engineering, with a strong portfolio of production-grade geospatial applications.
- Proven experience deploying cloud solutions on both AWS and Azure.
- Proficiency in Python, TypeScript, or modern JS frameworks (React, Next.js, etc.).
- Proven experience in front-end development for geospatial or data-rich interfaces, including building intuitive, high-performance dashboards.
- Demonstrated proficiency using AI-assisted development tools (Cursor, Claude Code, GitHub Copilot, etc.) with tangible examples of increased velocity or quality.
- Strong understanding of API architecture, distributed systems, CI/CD pipelines, and DevOps best practices.
Responsibilities
- Architect and develop core systems for the Pipeline Intelligence Suite, integrating multi-sensor geospatial data (imagery, LiDAR, satellite, drone) into scalable, high-performance applications.
- Build and deploy cloud-native and on-prem solutions across both AWS and Azure, ensuring resilience, scalability, and data integrity.
- Lead front-end development of client-facing dashboards and in-plane interfaces, designing intuitive, high-performance UIs that surface insights clearly and drive adoption.
- Collaborate with AI engineers and data scientists to operationalize object-detection, change-detection, and predictive-risk models.
- Design APIs, data pipelines, and services to process and visualize geospatial intelligence in near real-time.
- Rapidly prototype and iterate MVPs, validating new features directly with internal and external users.
- Leverage AI-enhanced development tools like Cursor, Claude Code, and/or GitHub Copilot to 10× productivity, automate workflows, and accelerate delivery.
Other
- Expected Travel: 10%
- Fully Remote
- Mentor peers and help build a small, high-leverage internal team around AI-first, geospatial-driven engineering excellence.
- Apply creative thinking to every problem — designing solutions that balance speed, accuracy, and operational practicality.
- A technologist with strong engineering instincts, curiosity across the full data stack, and an interest in geospatial
