Key skills
Geospatial dataPythonH3 indexingSpatial statisticsSpatial data pipelinesBackend systemsData analysis at scaleMCP tool interfacesAI evaluation frameworksGeospatial analyticsSecurity+ CertificationAILLMRAGPandasNumPyAnalyticsDatabricksFastAPIPytestpoetryProject ManagementCommunication
About this role
NV5 is a global technology solutions and consulting services company seeking a Spatial Reasoning Engineer to join their team of geospatial, AI, and data science professionals. The role focuses on developing a Model Context Protocol-based spatial reasoning platform, emphasizing the core AI spatial analytics layer and building production-grade analytical tools.
Responsibilities:
- Translate business requirements into technical specifications
- Support the development and evolution of the spatial reasoning core of our AI tool, including:
- H3 driven spatial analytics pipelines
- Spatial aggregation, density estimation, and hotspot detection
- Proximity, adjacency, and neighborhood analysis
- Deterministic, reproducible spatial reasoning functions
- Performance-optimized algorithms for large datasets
- Spatial correctness tests and benchmarking suites
- Deploy monitoring tools to track status and performance of system architecture and data flows
- Develop API-driven backend services with FastAPI, Pydantic, and async Python
- Work with columnar analytics stacks (DuckDB, PyArrow, Parquet / GeoParquet)
- Conduct vectorized data processing using NumPy, pandas, Polars
- Develop spatial computation with H3, Shapely, and lightweight geospatial utilities
- Write testable, benchmarked code using pytest and async test patterns
- Use profiling and performance tools to reason about memory, CPU, and data layout
- Build with python package managers like uv and poetry utilizing pyproject.toml for project management
- Collaborate in open-source–style repositories with linting, formatting, typing, and CI expectations
Requirements:
- Experience working with Geospatial data
- Strong Python engineering experience in production systems
- Hands-on experience with H3 or similar spatial indexing systems
- Proven ability to design efficient spatial data pipelines
- Experience working with spatial data analysis at scale
- Solid understanding of spatial statistics and spatial analysis concepts
- Comfort working in backend systems that integrate with LLMs and AI
- Strong focus on correctness, reproducibility, and explainability
- Strong written and verbal communication skills
- Familiarity with MCP-style tool interfaces
- RAG and embeddings AI application development experience
- Experience designing benchmark and AI evaluation frameworks
- Background in geospatial analytics outside traditional GIS stacks
- Experience integrating LLM services via clean Python interfaces
- Experience with data lakehouse platforms such as Databricks
- Understanding of geospatial metadata requirements
- Security+ Certification