Staff Software Engineer (Geospatial & AI)

Michael Baker International•United States,

7d•$130,000 - $149,600•Remote

About The Position

Michael Baker International is seeking a Staff Software Engineer Geospatial & AI to join the DATAMARK Technologies team in a fully remote capacity, supporting clients and operations across the United States. In this senior individual contributor role, you will lead the design and development of cloud-native geospatial applications with deeply integrated AI capabilities, drive autonomous workflow engineering, and shape the AI-assisted development practices that define how the team builds and ships software. You will bring technical depth across full-stack development, geospatial platforms, and enterprise AI tooling — and you will apply that expertise to build systems that perform inside mission-critical public safety and enterprise environments. This is a remote work schedule with no assigned office location. No sponsorship is provided for this role; all candidates must be eligible to work for any employer in the United States without restrictions indefinitely.

Requirements

Bachelor's Degree in Computer Science, Engineering, or a related field
5+ years of full-stack web application development experience
Proficiency in TypeScript and modern frontend and backend frameworks
Hands-on experience with geospatial technologies, including Esri, MapLibre, Mapbox, or equivalent platforms
Experience with AWS cloud platform and serverless architectures
Solid understanding of microservices architecture and RESTful API design patterns
Experience with relational and spatial databases; PostgreSQL and PostGIS preferred
Proficiency with version control systems and agile development methodologies

Nice To Haves

Experience building AI-powered features, agentic workflows, or LLM integrations at production scale
AWS Developer Associate or AWS Cloud Practitioner certification
Familiarity with indoor mapping standards or public safety GIS workflows
Knowledge of CI/CD automation and infrastructure-as-code practices

Responsibilities

Deliver scalable, AI-native microservices and full-stack geospatial applications that meet performance, reliability, and security standards for mission-critical deployment environments.
Lead the integration of AI and machine learning capabilities into geospatial applications using enterprise AI platforms, ensuring production-grade quality and measurable operational impact.
Develop autonomous AI systems for spatial data quality validation, geospatial analysis, and automated workflows that reduce manual intervention and increase data fidelity.
Drive the AI-assisted developer operations practice forward by owning agent frameworks, intelligent DevOps tooling, and automated code review pipelines that accelerate team velocity.
Architect serverless solutions and RESTful APIs for geospatial data services, ensuring scalability, maintainability, and alignment with modern API design standards.
Implement and optimize CI/CD pipelines using infrastructure-as-code principles, achieving consistent, repeatable, and auditable delivery across environments.
Execute integrations with enterprise GIS platforms and spatial data processing systems, ensuring data flows are accurate, performant, and interoperable across the technology stack.
Strengthen the team's engineering capability through active mentorship, rigorous code reviews, and the establishment of best practices that raise collective technical standards.
Ensure security guardrails, multi-tenant isolation, and compliance controls are embedded into AI-powered features from design through deployment.
Maintain accountability for the overall health, quality, and evolution of geospatial and AI engineering deliverables across the products you own.