Senior Software Engineer - Data Acquistion (Field Team)

Exodigo is the leading underground mapping solution for non-intrusive discovery. Our platforms combine multi-sensor fusion, 3D imaging, and AI technologies to create complete, accurate underground maps that enable confident decision-making for customers across the built world. We transform the project lifecycle for our customers, who include key community stakeholders in the utilities, transportation and government sectors. We are experiencing sky-rocketing growth and closed a historically large $96M Series B round in July of 2025 .

Requirements: • 7+ years of experience building, operating, and owning production-grade backend platforms in data-intensive environments. • Strong proficiency in Python or an equivalent high-level language, with the ability to write clear, maintainable, and robust production code. • Hands-on experience with Linux-based systems and networking fundamentals . • Significant experience in designing architecture and building complex, data-intensive distributed systems , with the ability to balance reliability, performance, and scalability tradeoffs. • System-level thinking - ability to reason about end-to-end flows, state, and failure modes, proactively identifying gaps, risks, and opportunities and translating them into robust, production-grade solutions with observability built in from day one. • Ability to operate effectively in a fast-moving environment, and to thrive in a complex multidisciplinary domain where requirements are not always fully defined and engineering judgment plays a central role in shaping solutions. • Strong ownership mindset and communication skills , with a collaborative approach, technical maturity, and a continuous learning attitude. Additional nice to have requirements: • Experience with Rust/C/C++ or embedded systems development - Strong advantage • Background in hardware-software integration, sensors, or data acquisition systems - Strong advantage • Hands-on experience with AWS and cloud infrastructure in production environments, including deployment, monitoring, and operations. • Experience working with geospatial data and/or positioning technologies (e.g. GNSS). • Experience leveraging AI-assisted workflows and tools to improve development velocity, code quality, or system design in production environments.