Software Engineer (Civil Aviation)

About the role

The role centers on backend systems for U.S. national airspace safety and efficiency. You will own the design, implementation, and operation of critical backend services that process high-velocity data streams. The work involves uncertainty modeling and data provenance reasoning within dynamic, safety-critical contexts. You will collaborate closely with domain experts to translate aviation requirements into robust software solutions. A significant part of the role involves maintaining and extending systems without prior involvement in their creation. Clear communication of technical decisions in plain language is essential for success in this position. You will work within cross-functional, mission-critical teams where reliability and correctness are non-negotiable.

Key facts

What you'll do

A backend platform operates at the center of U.S. airspace decision-support and must meet stringent reliability standards. You will maintain and extend backend services that handle real-time data ingestion, processing, and distribution. Uncertainty modeling and data provenance reasoning occur within dynamic, safety-critical contexts where data is always an approximation of the physical world. You will implement data integration, storage, and processing pipelines that ensure correctness and traceability. Cross-team collaboration functions within a mission-critical environment that supports national airspace safety and efficiency. You will work with modern data storage systems, designing schemas and interfaces that balance performance with maintainability. AWS and cloud-native architecture experience is necessary to deploy and operate resilient services. Exposure to high-availability systems, such as "four nines" reliability, is a strong plus for this role. You will use design principles that strongly influence maintainability, scalability, and performance across distributed components. Modern LLM tools improve development workflows and code quality, and you will leverage them where appropriate.

Requirements

A Bachelor's degree is held and is mandatory for this position.

Experience building production-grade backend or distributed systems exists and must be demonstrable.

Design principles strongly influence maintainability, scalability, and performance in all implemented solutions.

Proficiency in at least one modern programming language is demonstrated through shipped systems or significant projects.

Learning Rust and Python from a strong foundation is expected, as these languages form the core of the tech stack.

Experience with data integration, data storage, data processing, and data modeling systems exists and is essential.

AWS and cloud-native architecture experience is required to operate services in production environments.

Exposure to high-availability systems, such as "four nines" reliability, is a strong plus.

Functioning effectively in complex, multi-system environments with evolving data models is required on a daily basis.

Clear communication and cross-team collaboration occur in a mission-critical setting and are evaluated regularly.

Practical notes

Employment offers depend on timely U.S. authorization for required duties.

U.S. work authorization and the ability to obtain required clearances are mandatory.

Typical interview steps

Hiring for engineering roles usually starts with a recruiter screen, followed by one or two technical rounds. Candidates often solve a coding problem, discuss past projects, and answer system design questions. Some loops include a take-home task. Final rounds typically cover team fit and give candidates a chance to ask questions. Interviewers look for how you break down an unfamiliar problem, not just whether you reach the answer. Practicing a few problems aloud and reviewing your own past projects are the best preparation.

Good to know

Work centers on aviation and critical infrastructure decision-support systems.

The tech stack includes Rust and Python for backend services.

Data fusion and uncertainty modeling are core problem domains.

High-reliability systems are a standard expectation.

Modern development workflows incorporate LLM-assisted tooling.

Questions to ask

Good questions to ask the employer in the interview: what does success look like in the first six months, how is the team structured, what is the current biggest challenge, and how are decisions made. Asking about growth paths and the review process is also well received. Employers expect questions, and good ones show preparation.

Career growth

Engineering careers usually progress from individual contributor to senior, staff, and principal levels. Some engineers move into management and lead teams of five to twenty people. Others stay on the technical track. Growth follows demonstrated impact, not tenure alone. A typical engineering ladder has clear levels with defined expectations for scope, quality, and mentorship. Moving up usually requires owning outcomes end to end rather than completing assigned tickets.