Principal Artificial Intelligence Software Engineer
$141,250–$211,900 year
On-siteSeaTac, Washington, United States
Job Summary
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 and operational efficiency. Design and build the AI platform enabling organizational self-service while maintaining ownership of system performance, reliability, and continuous improvement. Exercise considerable latitude to solve ambiguous, high-impact challenges, including scaling AI from pilot to production, integrating AI into legacy operational systems, and defining governance approaches for novel use cases. Make decisions on technical architecture, sourcing strategies, and initiative sequencing based on business impact and organizational readiness. Influence cross-functional prioritization and adoption by stakeholders across IT, business, and governance teams to ensure secure, compliant integration. Partner with Product Management to integrate AI solutions into roadmaps, ensuring technical feasibility and value alignment. Ensure production excellence through monitoring, evaluation frameworks, and optimization strategies that enable systems to meet performance targets. Develop technical talent and set engineering standards through mentorship and knowledge sharing. Drive innovation through AI research and experimentation, presenting findings to executive leadership.
Required Qualifications
- 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.
- Must be able to lift 50 lbs
Desired Qualifications
- 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 measurable business impact
- Experience upskilling engineering and product teams from traditional software development to AI native workflows
- Experience developing accessible technologies
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