AI & GIS Solutions Consultant

Corner Alliance

Consultant designing and integrating geospatial components of agentic AI systems for federal government client. Collaborate with stakeholders to ensure authoritative and compliant alert-area geometry.

Posted 7/29/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in geospatial software development and GIS analysis, with a strong focus on Esri ArcGIS, REST API design, and geospatial data standards. Proficient in Python, JavaScript, and SQL, with experience in secure cloud environments and AI/ML integration.

Highest-signal resume keywords

Esri ArcGIS ProGeospatial Software DevelopmentREST API DesignPython ProgrammingGeospatial Data Standards

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Geospatial Data EngineeringGeoJSONShapefilePolygon GeometryTopology ValidationSQLCloud PlatformsAI/ML SolutionsContainerizationCI/CD Practices

Soft Skills

Analytical SkillsDocumentation SkillsCross-Functional Communication

Tools & Technologies

AWSArcGIS OnlineArcGIS API for PythonArcGIS API for JavaScriptDockerGit

Industry Keywords

Geospatial EngineeringNIST AI RMFNIST 800-53FCC WEA Geo-Targeting RulesHuman-in-the-Loop Controls

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformJavaScriptPythonSQL

About the role

Key responsibilities & impact

Architect and build the Polygon and Geo-Targeting Agent, importing authoritative hazard geometry — NWS warning polygons, wildfire perimeters, plume models, and jurisdictional GIS layers — and managing pre-drawn, jurisdiction-vetted evacuation zones
Build on Esri ArcGIS as the geospatial foundation, consistent with the platform alerting vendors already build on
Develop deterministic geometry validation logic detecting self-intersections, slivers, holes, and duplicate points
Design and maintain authoritative alert geometry storage in CAP and GeoJSON vector form
Develop REST API endpoints for the geospatial agent, including /importGeometry, /validatePolygon, and /suggestGeoLanguage, following the same vendor-agnostic, CAP-centric pattern as the co-pilot's message endpoints
Build overshoot/undershoot analysis that compares proposed polygons to hazard footprints and surfaces the over- vs. under-alerting tradeoff to alert originators before send
Ground and test the agent against real geometry and incorporate feedback from GIS practitioners and alert originators
Coordinate with the broader Warning Author agent architecture (MDD, Pre-Incident Template, CAP Validation, and Continuous Learning agents) to keep geospatial and message-drafting behavior consistent
Apply prompt engineering and agentic/RAG techniques where the LLM phrases geo-targeted language (e.g., locally recognized streets, landmarks, zone names)
Implement secure, compliant cloud hosting (AWS government-compliant environment) with human-in-the-loop controls, data minimization, and audit logging aligned to NIST AI RMF and NIST 800-53
Document system architecture, data models, geometry validation rules, and APIs; participate in stakeholder demos, technical reviews, and working groups
Carry out our Commitments to Deliver, Grow, and Thrive

Requirements

What you’ll need

Bachelor's degree or higher in GIS, geography, geospatial engineering, computer science, data science, or a related field
Five or more years of experience in geospatial software development, GIS analysis, or geospatial data engineering
Hands-on experience with Esri ArcGIS (ArcGIS Pro, ArcGIS Online/Enterprise, ArcGIS Location Platform, and/or the ArcGIS API for Python or JavaScript)
Working knowledge of geospatial data standards and formats: GeoJSON, Shapefile, vector polygon geometry, and topology validation (self-intersections, slivers, hole detection, polygon simplification)
Proficiency with Python, JavaScript, and SQL; experience with at least one major cloud platform (AWS preferred, Azure, or GCP), including secure/government-compliant environments
Experience designing and integrating REST APIs for geospatial or structured-data services
Some hands-on exposure to AI/ML or LLM-enabled solutions (prompt engineering plus retrieval-augmented generation or agentic workflows), sufficient to collaborate closely with the AI/LLM engineering team
Ability to translate stakeholder and policy requirements (e.g., FCC WEA geo-targeting rules) into technical geospatial features and validation logic
Working knowledge of containerization (Docker), version control (Git), and CI/CD practices
Strong analytical, documentation, and cross-functional communication skills
US citizenship or permanent resident and the ability to pass public trust clearance or suitability

Benefits

Comp & perks

401k matching (4%)
PTO (3 weeks to start, 4 weeks (2-5 years) and 5 weeks (5 years+))
health, dental, vision
short- and long-term disability
FSA accounts
4 weeks of paid parental leave
11 paid holidays (including your birthday off)
fitness & cell phone reimbursements
monthly all hands update meetings
annual in-person all hands team building day and evening out
regular check-ins for professional growth goals
semi-monthly one on one performance manager meetings
a social team that coordinates monthly events
use of technology like Slack to keep us connected and collaborative
overall, a company culture dedicated to a highly engaged team