AI Engineer IV

As an AI Engineer IV
, you’ll provide technical leadership to a team building AI/ML solutions that tackle complex business problems—from early concept and experimentation through secure, scalable production deployment. You’ll shape AI strategy, guide solution design, and lead the delivery of high‑impact capabilities across data pipelines, model development, and AI‑enabled services. This hybrid role is located on our campus in Mountlake Terrace, Washington.

• Architect and deliver AI systems end‑to‑end. Recommend and develop comprehensive systems and frameworks for AI applications and products, balancing speed to value with reliability and maintainability.
• Lead ideation and rapid validation. Pitch concepts to leadership, then lead the design and build of prototypes and minimum viable products to validate AI/ML solutions before scaling investment.
• Shape cloud architecture for complex AI platforms. Contribute to designing and implementing cloud architecture for large, multi‑faceted AI systems (compute, storage, security, deployment, monitoring).
• Enable robust data foundations. Assist in the design and scaffolding of scalable data pipelines that power advanced AI systems and enable model lifecycle improvements.
• Operationalize AI via services and APIs. Define specifications for low‑latency APIs/services that deploy models and integrate AI into enterprise applications.
• Build monitoring and reliability into production. Develop code and approaches for monitoring models and AI systems to ensure consistent performance, accuracy, and reliability in production.
• Driving engineering excellence. Participate in principled, agile‑like development practices; ensure peer review for all assigned work and conduct reviews for others as needed.
• Document with production discipline. Create and maintain thorough documentation aligned with team procedures, SDLC expectations, and corporate policies.
• Mentor and raise the bar. Guide AI engineers on AI/ML best practices and help grow team capability through feedback, coaching, and knowledge sharing.
• Influence strategy and roadmaps. Advise team and division leadership on enterprise AI strategy, AI technology roadmaps, and AI infrastructure direction.
• Partner with stakeholders and uphold governance. Collaborate with external stakeholders to conceptualize AI solutions that deliver business value while adhering to AI governance, best practices, and data quality/security standards.
• Provide thought leadership. Contribute to the broader AI community through best‑practice sharing, patterns, reusable frameworks, and technical leadership.
• Perform other duties as assigned.

• Bachelor’s degree in computer science, Information Systems, Statistics, Mathematics, or a related field, or equivalent experience.
• At least 8+ years of relevant experience in software development, including knowledge of the software development lifecycle and proficiency in multiple programming languages, and industry experience developing, deploying, and maintaining AI/ML systems.

• Experience building AI solutions using cloud platforms and services (e.g., Azure AI services or similar) in a highly regulated environment; healthcare experience preferred.
• Experience successfully product ionizing AI models, including scalable pipelines and robust monitoring systems.
• Strong background developing deep learning models using modern frameworks (e.g., Tensor Flow, PyTorch, MLX).
• Experience with software design patterns, microservices, distributed systems, and container orchestration.
• Knowledge of ethical AI practices (explainability, fairness, bias mitigation) and applying them in real solutions.
• Experience implementing advanced LLM solution patterns (e.g., retrieval‑augmented generation and structured reasoning approaches) and setting team best practices through reviews and standards.

• Proven experience developing deep learning architectures (e.g., transformers, CNNs, GANs, LSTMs, GNNs, autoencoders, diffusion models, NODEs).
• Proven ability to debug and optimize AI systems, including performance analysis and tuning approaches.
• Strong software engineering…