Software Engineer, Data Core

Who We Are 4M Analytics is building the first Subsurface World Model: an AI platform that uses visual reasoning and large-scale data fusion to turn the undocumented world beneath our streets into one living, intelligent map. We make reliable utility data accessible to the construction industry, government agencies, and utility owners, and we are changing how infrastructure is understood and protected. We are Series C, backed by Insight Partners, Viola, and F2, with 120 people across Tel Aviv and Austin, Texas. The problem is massive, the momentum is real, and we are moving fast. The Opportunity We're seeking an experienced Software Engineer with a strong background to become an integral member of our Data-Core team, tasked with the mission of processing, structuring, and analyzing hundreds of millions of data sources. Your role will be pivotal in creating a unified, up-to-date, and accurate utilities map, services, and applications for accelerating our mapping operations. Your contributions will directly impact our core product's success. Our R&D division champions an AI-assisted development model, leveraging modern code-generation tools to streamline implementation. In this role, you will be empowered to focus primarily on high-level architecture, system design, and complex problem-solving. What You'll Do Collaborate with cross-functional teams to design, build, and maintain data processing pipelines while contributing to our common codebase. Contribute to designing and implementing data architecture, ensuring effective data storage and retrieval. Develop and optimize complex Python-based applications and services to allow more efficient data processing and orchestration, enhancing the quality and accuracy of our datasets. Drive the scalability and performance optimization of data systems, addressing infrastructure challenges as data volume and complexity grow. Create and manage data infrastructure components, including ETL workflows, databases, supporting seamless data flow and accessibility. Design and implement CI/CD processes for data processing, model training, releasing, testing and monitoring, ensuring robustness and consistency. Implement geospatial data processing techniques and contribute to the creation of our unified utilities map, enhancing the product's geospatial features. Own your components end-to-end, from design through production, monitoring and on-call, and drive improvements without waiting to be asked. What You Bring Bachelor's degree in Computer Science, Engineering, or a related field. 5+ years of experience in software engineering with a focus on data systems. Proficiency in Python. Experience with big data technologies like Hadoop, Spark, or Kafka. A track record of ownership: you’ve taken a system or project from an ambiguous problem to production and stayed accountable for it after launch. Experience leading technical initiatives, such as driving design decisions, aligning stakeholders across teams, or mentoring other engineers. AI-First Mindset We are building an AI-first engineering culture, and we're looking for engineers who are genuinely excited about working this way. In practice, this means: You're well versed in using AI tools in your work — code assistants, LLMs, or AI-augmented workflows. You enjoy handing off code-writing to tools, so you can focus on complex system design. You see AI not as a threat to engineering craft, but as a multiplier of it. Specific tools and methods can be learned together. What matters is the mindset and the motivation to grow into this way of working. Standout Attributes Founding mindset: You have built products from scratch, either side projects, open-source tools, or zero-to-one engineering systems, and you know how to balance speed with technical quality. Geospatial experience: you’ve worked with spatial data and tooling (e.g., PostGIS, GDAL, Shapely, GeoPandas) and understand projections, topology and spatial indexing.