Lead Engineer needed for AI-driven wildlife monitoring non-profit

---

---

Lead Software Engineer (Part-Time, Remote Contract) About WildTrack: WildTrack is an award-winning, fast-growing nonprofit based in the Research Triangle area of North Carolina. We protect wildlife by developing and applying non-invasive, AI-powered monitoring technologies that support conservation efforts around the world. Our team includes dedicated professionals and volunteers who care deeply about making a real-world impact through science, data, and innovation. We value flexibility, autonomy, and a collaborative, multidisciplinary environment that supports both balance and productivity. About the Role: We’re looking for a Lead Software Engineer, excited to apply their technical skills to a mission-driven organization building technology to support wildlife conservation. While a background in wildlife conservation isn’t required, an interest in using technology for real-world impact is essential. As Lead Software Engineer, you will be responsible for driving the day-to-day development of our platform and mobile app, WildTrackAI. You’ll work closely with the Technical Program Manager to lead a small team of contractors and volunteer engineers, translating technical requirements into actionable development tasks and ensuring timely, high-quality execution. This is a hands-on role focused on implementation, coordinating engineering workflows, maintaining code quality, and aligning development with the broader technical direction of the organization. This is a new, remote fractional role: 20 hours per week on a 6-month contract, with $20,000 in compensation for the initial term. There is strong potential for renewal or transition to full-time based on performance and funding. Key Responsibilities • Collaborate with the Technical Program Manager to translate technical requirements into clear, actionable development tasks • Lead day-to-day engineering execution across the WildTrackAI platform and mobile app • Coordinate a distributed team of contractors and volunteer engineers, ensuring smooth collaboration and task ownership • Review code and frontend/UI components for quality, security, maintainability, and consistency; uphold best practices across the team • Manage and maintain code repositories, CI/CD workflows and AWS infrastructure to ensure the system’s overall scalability, reliability, and long-term maintainability • Monitor development progress, identify blockers early, and keep engineering work aligned with project priorities and timelines • Contribute hands-on to the codebase, primarily backend (Python/Flask), with occasional frontend/mobile work as needed • Support the selection, onboarding, and mentorship of volunteer engineers to strengthen team capacity and effectiveness • Stay current with relevant technologies and recommend improvements when beneficial Requirements: • 5+ years of backend development experience (Python/Flask), with some familiarity across the stack • Comfortable working with full-stack technologies such as Python, Flask, Flutter, AWS (Lightsail, RDS, Lambda, S3), Docker, PostgreSQL, and GitHub • Experience with quality assurance practices, including writing and executing tests • Familiarity with tools like Figma, Storybook, and Chromatic for UI development and review • Experience managing CI/CD pipelines and DevOps workflows using GitHub Actions and AWS infrastructure • Exposure to data engineering concepts (ETL pipelines, data modeling, storage optimization) • Excellent communication skills for effective collaboration in an asynchronous, remote work environment Good to have: • Experience in the development and deployment of machine learning and computer vision systems • Experience working with designers to translate UI/UX systems into scalable, reusable components • Strong front-end development experience using React for web applications • Mobile app development experience using Flutter for iOS and Android

Keyword: Python

Price: $20.0

Python AWS Lambda PostgreSQL CI/CD UX & UI Mobile App Development Artificial Intelligence Machine Learning