Sr. Python Engineer
Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on Oct 15, 2026. Airspace Link scores B on the Alion truth index.
Description
About the Company
Throughout history, transformative advancements in infrastructure have propelled humanity forward-from Vanderbilt’s railroads to Edison’s electrical grid and Eisenhower’s highways. Today, we stand at another pivotal infrastructure moment with Airspace Link’s drone (UAS) infrastructure platform, the backbone for integrating drones safely and seamlessly into the national airspace.
As an FAA-approved Unmanned Aircraft Systems Service Supplier (USS), our flagship cloud platform, AirHub® Portal, provides a comprehensive solution for businesses and government entities seeking to safely manage and scale drone operations across the United States.
Founded in Detroit in 2018, Airspace Link is an award-winning, high-growth, VC-funded startup backed by Altos Ventures, Avanta Ventures, and others. With a remote-first culture, we are driven by our mission to advance the UAS industry while creating an environment where people of diverse backgrounds and perspectives thrive as engineers, UAS consultants, creative thinkers, and passionate innovators.
Job Summary
Do you want to help build the digital infrastructure that will power the future of autonomous aviation? At Airspace Link, we are building the technology that enables drones to safely integrate into the national airspace. Our platform supports cities, government agencies, and enterprises as they launch and scale drone programs that improve public safety, enhance operational efficiency, and unlock new capabilities.
As a Sr. Python Engineer, you will build the backend services and distributed systems that power AirHub® Portal. You will build scalable systems that support complex workflows, geospatial data, and mission-critical operations while helping shape the future of the rapidly evolving UAS industry.
You will partner closely with engineers across Platform, Data, Product, and Infrastructure teams, as well as product managers and domain experts, to deliver reliable, scalable, customer-focused solutions. This is an opportunity to work at the intersection of cloud computing, geospatial technology, aviation, and emerging mobility.
Technology Stack
- Our engineering teams work with modern cloud-native technologies, including:
- Python
- Go (Golang)
- Microsoft Azure
- Kubernetes
- PostgreSQL
- Kafka
- Azure Event Hubs
- REST and gRPC APIs
- Grafana
- VictoriaLogs
- Cloud-native CI/CD practices
- Distributed systems architecture
- Containerized applications
Engineering Environment
Airspace Link engineers have meaningful ownership over the products and systems they build. We work in two-week Agile iterations and encourage engineers to influence technical direction, architecture, and product outcomes.
Engineers are responsible not only for writing code, but also for understanding customer needs, improving system reliability, participating in technical decisions, and delivering measurable value.
Our engineering teams are organized around key product and platform areas, including:
- Data & Analytics
- Platform
- Product Applications
- APIs and Backend Services on UAS Traffic Management (UTM)
Engineers have opportunities to collaborate across teams and contribute to a broad range of technical challenges.
Location: Remote (anywhere in US) or Hybrid (for MI residents)
Benefits & Perks: Airspace Link offers a comprehensive benefits package that includes medical, dental, vision, 401(k), gender neutral parental leave, generous time off, and much more. For more information, please check out www.airspacelink.com/careers
Requirements
What It Takes to Be Successful in the Role:
- Bachelor’s degree in Computer Science, Mathematics, or related field, or equivalent level of experience
- 7+ years of experience working on a production SaaS applications or APIs in the backend, using Python
- Experience working with large and diverse datasets (tabular, geospatial, vector, raster, point cloud)
- Strong knowledge of software design patterns and unit testing
- Steam processing and big-data computation experience in a cloud environment, with Databricks/Spark strongly preferred
- Exposure to Azure Functions, containerization on Kubernetes, serverless or microservice architectures