Geospatial Platform Engineer: AI/ML & Secure Cloud

val's services; McLean (VA); On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

401(k)

Mental health resources

Unique perks

Job summary

val's services is seeking a Geospatial Platform Engineer to develop, deploy, and support geospatial, imagery, AI/ML, and data-driven applications in secure hybrid environments. You will create backend services, APIs, and platform components for mission-focused workflows.

Responsibilities include building data ingestion and analytic services, designing containerized architectures with Docker and Kubernetes, and automating infrastructure using Ansible and Terraform.

Qualifications

• Bachelor's degree in a relevant field and 6+ years of experience, or higher degrees with fewer years.
• Active TS/SCI security clearance with polygraph; US citizenship required.
• Proficiency in Python, Java, C++, SQL, Bash.
• Experience with containerization, cloud, and secure DevSecOps practices.
• Ability to work independently and collaborate across technical teams.

Responsibilities

• Develop backend services, APIs, and platform components for mission-focused workflows.
• Build data ingestion, transformation, indexing, and analytic services.
• Design and maintain containerized architectures using Docker and Kubernetes.
• Create CI/CD pipelines and automate infrastructure with Ansible and Terraform.
• Support geospatial visualization and AI/ML model deployment at scale.
• Troubleshoot complex system issues across environments.

Skills

Python

Java

C++

SQL

Bash

DevSecOps

Education

Bachelor's in a relevant field

Tools

Docker

Kubernetes

Ansible

Terraform

PostgreSQL

PostGIS

Elasticsearch

Job description

val's services is seeking a Geospatial Platform Engineer to develop, deploy, and support geospatial, imagery, AI/ML, and data-driven applications in secure hybrid environments. You will create backend services, APIs, and platform components for mission-focused workflows.

Responsibilities include building data ingestion and analytic services, designing containerized architectures with Docker and Kubernetes, and automating infrastructure using Ansible and Terraform.