Principal AI Engineer

ForeFlight•Austin, TX

About The Position

Jeppesen ForeFlight builds industry-leading aviation software used by pilots, aircraft operators, and major airlines worldwide. As a high-growth, private equity-backed company, we are focused on scaling our operations, strengthening our financial infrastructure, and driving operational excellence across the business. Our team combines deep domain expertise with a collaborative, high-performance culture to solve complex challenges and support continued growth. Jeppesen and ForeFlight are looking for a Principal Engineer to lead the next evolution of software development inside our organization: agentic coding, AI-native engineering workflows, and large-scale adoption of AI engineering systems. This is not a traditional platform engineering role. We are looking for a deeply technical builder and change agent who has lived through high-velocity AI-enabled development environments and can help transform how engineering gets done across our company. You will partner directly with the CTO and senior engineering leadership to define the strategy, tooling, standards, and operating model for AI-assisted software development. Your mandate is to dramatically improve engineering velocity, quality, and leverage through practical adoption of coding agents, LLM-powered workflows, and AI-native engineering practices. This role is also fundamentally about elevating and evolving our existing engineering organization. We are looking for a leader who can help current developers successfully adopt AI-native coding practices, modern engineering workflows, and agentic development tools in a practical, scalable, and measurable way. Success will require both deep technical expertise and the ability to influence, coach, and upskill engineers across a broad range of experience levels. Aviation domain expertise is not required. We are prioritizing candidates who bring fresh thinking from AI-forward engineering cultures and companies that are already operating at the forefront of AI-enabled software development.

Requirements

Deep software engineering background with experience operating at principal, staff-plus, or equivalent technical leadership levels
Proven experience using AI coding systems in production engineering environments
Hands-on experience with modern coding agents and AI development workflows
Strong systems thinking and ability to influence engineering organizations at scale
Track record of introducing transformative developer tooling, engineering platforms, or workflow improvements
Ability to balance experimentation with operational rigor, security, and engineering quality
Exceptional communication, mentoring, and technical leadership skills
Passion for helping engineering teams evolve and adapt to AI-native ways of working

Responsibilities

Define and lead the company-wide strategy for agentic coding and AI engineering enablement
Evaluate, prototype, and operationalize AI coding agents and AI-native developer tooling
Drive adoption of tools and workflows that materially improve developer productivity, software quality, and engineering velocity
Lead the cultural and technical adoption of AI-assisted software development across the engineering organization
Upskill and mentor existing engineering teams on effective use of coding agents, LLM-based workflows, and AI-native development practices
Develop training, playbooks, standards, and internal best practices for AI-enabled engineering
Identify opportunities where AI can augment—not replace—developer effectiveness and creativity
Help engineers transition from traditional development workflows to AI-accelerated engineering models
Build enthusiasm, trust, and practical competency around AI tooling through hands-on leadership and measurable results
Establish best practices for: AI-assisted software development, autonomous and semi-autonomous coding agents, prompt engineering for software delivery, human-in-the-loop review systems, AI-assisted testing, debugging, and refactoring
Build internal frameworks and governance around safe and effective use of AI in engineering
Partner with engineering leaders to redesign workflows, SDLC processes, and developer experience around AI capabilities
Create measurable productivity and quality metrics tied to AI tooling adoption
Serve as a technical advisor to the CTO and executive leadership on emerging AI engineering trends
Influence architecture and platform direction to maximize compatibility with AI-driven development systems