Principal Artificial Intelligence Software Engineer

Company

Alaska Airlines

Guided by our purpose, core values, and leadership principles, we are creating an airline people love. Our corporate teams set the strategies and operational plans to ensure the success of our company. Whether we use our expertise in accounting, human resources, finance, planning, legal, marketing, or any of our operational divisions, our shared passion for travel and our guests is what motivates us to achieve excellence each day.

If you share our passion for creating an airline people love, we want to hear from you.

The Principal Artificial Intelligence (AI) Software Engineer role is the sole subject matter expert in production-grade AI systems, platform architecture, and applied AI governance. (process/discipline in the company). As an individual contributor, this role defines long-term strategy for AI adoption, technical standards, and cross-functional integration (process/discipline) and exercises considerable latitude and initiative to solve highly ambiguous, high-impact challenges that advance Alaska Airlines’ operational excellence, commercial differentiation, and AI maturity (complex problems).

• Architect and lead end-to-end development and deployment of AI solutions leveraging LLMs, generative AI, and agentic technologies, establishing reusable architectures and patterns that drive automation, operational efficiency, and strategic business outcomes.

• Design and build the AI platform that enables organizational self-service, maintaining ownership of system performance, reliability, and continuous improvement of AI capabilities.

• Exercise considerable latitude and initiative to solve ambiguous, high-impact challenges where problem definition, solution approach, and success criteria require significant discovery, including scaling AI from pilot to production, integrating AI into legacy operational systems, and defining governance approaches for novel AI use cases.

• Make decisions on technical architecture, sourcing strategies including build, buy, or partner approaches, and sequencing of AI initiatives based on business impact, technical feasibility, and organizational readiness, setting direction that shapes how AI is delivered across Alaska.

• Influence across company and several levels up to lead cross-functional prioritization and adoption of AI initiatives by influencing stakeholders across IT, business, and governance, risk, and compliance teams to ensure secure, compliant integration into enterprise systems.

• Partner with Product Management and business leaders to integrate AI/GenAI solutions into product roadmaps, ensuring technical feasibility and business value alignment.

• Ensure production excellence by implementing monitoring, evaluation frameworks, and optimization strategies that enable AI systems to meet or exceed performance targets and deliver measurable business results.

• Develop technical talent and set engineering standards through mentorship, technical leadership, and knowledge sharing that elevates the capabilities of the AI Engineering Team.

• Drive innovation through AI research and experimentation including evaluation of emerging technologies, new data sources, and advanced methodologies, with presentation of findings to executive leadership.

• 7 years of experience in software development experience with demonstrated expertise in multiple programming languages (Python, Java, Golang, C++, or similar).

• Bachelor’s degree with a focus in Computer Science or an additional two years of relevant training/experience in lieu of this degree.

• High school diploma or equivalent.

• Minimum age of 18.

• Must be authorized to work in the U.S.

• 3+ years of experience leading technical architecture and design decisions for large-scale distributed systems, with demonstrated ability to evaluate emerging technologies and drive strategic platform investments through build vs buy decisions.

• 5+ years of experience designing, delivering, and operating ML/AI systems in production, including at least 2 years with Generative AI (LLMs, multi-modal models, agent frameworks, tool-calling, workflow orchestration systems).

• Demonstrated track record of leading cross-functional AI initiatives from concept through production adoption and scaling, including establishing monitoring, evaluation frameworks, and continuous improvement practices.

• Master's degree or PhD in Computer Science or related technical field.

• Experience designing ML/AI platforms that serve organization wide product and engineering teams.

• Published research, patents, technical blog posts, or conference presentations on AI/ML systems and architectures.

• Experience implementing AI governance frameworks including security controls, risk assessment, and adherence to industry standards.

• Track record of evaluating build vs buy decisions and successfully adopting emerging AI technologies (e.g., transformer-based models, agentic tool-use patterns, embedded inference) with…