Engineering Developer

Aircraft Performance Group•Lone Tree, CO

1d•Onsite

About The Position

We are looking for a skilled and driven Engineering Developer to join our team. As an Engineering Developer, you will research, design, and implement complex aviation computational algorithms, data processing tools, and chart-rendering software that power our core flight performance, operations, and aeronautical charting products. You will work in an AI-forward engineering environment where modern AI coding assistants and agentic workflows are part of how we build, review, and ship. The ideal candidate is a strong C#/.NET desktop and backend engineer (with PHP and Swift used across our wider product suite) who is fluent in 2D graphics rendering, geospatial computation, and the practical use of AI tooling to move faster without sacrificing rigor. You will work closely with aviation engineers, data specialists, and product managers to deliver high-quality, validated solutions that meet regulatory and operational standards.

Requirements

At least 3 years of professional software development experience.
Strong proficiency in C#/.NET and Windows desktop development (WinForms); working knowledge of PHP and Swift across the product suite.
Experience with 2D graphics and vector rendering (GDI+, SVG, and/or SkiaSharp), including pixel-accurate layout and text metrics.
Solid grasp of geometry, coordinate systems, and map projection math for spatial data placement.
Ability to research and interpret complex aviation regulations, performance standards, and operational requirements.
Proven experience designing, implementing, and optimizing mathematical models and algorithms for aviation performance calculations.
Strong background in structuring, validating, and optimizing large aviation datasets.
Ability to work from incomplete specifications and determine appropriate implementation methods.
Proficiency in designing modular, maintainable, and efficient computational workflows.
Experience with rigorous testing methodologies, including validation of algorithms against regulatory requirements.
Strong collaboration and communication skills, with the ability to explain technical concepts to both technical and non-technical stakeholders.
Proficiency with Git-based workflows, automated testing frameworks, and CI/CD pipelines.
Knowledge of secure coding practices and regulatory compliance in aviation-related systems.
Experience applying AI/ML techniques to real-world software applications beyond conversational interfaces (e.g., data modeling, algorithm optimization, anomaly detection, or predictive analytics).
Hands-on proficiency with AI-assisted development tools (Claude, Claude Code, GitHub Copilot, or similar), including effective prompting and disciplined verification of generated output.
Current, working knowledge of the rapidly evolving AI landscape - recent frontier model releases, their capabilities and trade-offs - and sound judgment on when and how to apply them.
Practical understanding of agentic and multi-agent (sub-agent) workflows: decomposing work, delegating to specialized agents, and verifying their output as part of a development pipeline.

Nice To Haves

Direct experience in aviation software development, flight performance calculations, or related computational engineering fields.
Experience building aeronautical charting, cartographic, or instrument-procedure depiction software.
Familiarity with FAA digital chart/procedure data sources and dual on-screen/export rendering pipelines.
Experience integrating LLM/AI APIs (e.g., Anthropic Claude) into product features, data extraction, or developer tooling workflows.
Experience running local or self-hosted AI models (e.g., Ollama, llama.cpp, LM Studio) for offline, cost-sensitive, or privacy-sensitive use cases.
Demonstrated personal enthusiasm for AI - self-directed learning, side projects, or independent experimentation that keeps pace with a fast-moving field.
Familiarity with aviation data standards (ARINC, IATA, ICAO) and integration with third-party data providers.
Experience in building performance simulation or flight modeling tools.
Understanding of numerical methods, optimization techniques, and computational efficiency in algorithmic implementations.
Exposure to multi-platform deployment with Swift for iOS-based flight tools.
A degree in Computer Science, Software Engineering, Applied Mathematics, or Aerospace Engineering (or equivalent experience).

Responsibilities

Research, design, and implement advanced algorithms for aircraft performance, weight and balance, runway analysis, and other aviation-specific computational areas.
Develop and maintain robust data processing tools to structure, validate, and optimize aviation datasets, including airport, aircraft, and environmental information.
Translate ambiguous or limited requirements into well-structured software solutions, determining the most effective methods of implementation.
Implement aviation domain knowledge into computational workflows, ensuring compliance with regulatory requirements (e.g., FAR, EASA, ICAO).
Collaborate with flight operations experts, software engineers, and data teams to ensure accuracy and real-world applicability of algorithms and tools.
Build and maintain scalable software modules in .NET, PHP, and Swift, ensuring performance, security, and maintainability.
Design and document system architectures, algorithm specifications, and data workflows.
Conduct validation and verification testing of computational tools against regulatory and operational benchmarks.
Participate in peer reviews, maintain high coding standards, and mentor peers on computational problem-solving best practices.
Investigate issues, troubleshoot computational anomalies, and implement solutions to ensure the reliability and integrity of calculations.
Stay current with industry trends, regulatory changes, and advancements in computational techniques relevant to aviation.
Design and maintain 2D rendering pipelines for aeronautical instrument charts and procedure plates, keeping on-screen (GDI+) and exported (SVG/PDF) output in exact visual parity.
Implement cartographic and geospatial geometry - coordinate projection, scaling, and layout math - to position navaids, fixes, routes, holding patterns, airspace, and procedure symbology accurately.
Parse and structure FAA instrument procedure data (approach, SID/STAR, circling, vertical profile) and integrate AI-assisted document extraction to convert source charts into structured, editable data.
Maintain versioned, backward-compatible save/layout file formats so previously authored work continues to load correctly across releases.
Leverage AI coding assistants and agentic tools (e.g., Anthropic Claude / Claude Code) to accelerate development, while rigorously reviewing, testing, and verifying all AI-generated code before it ships.