AI Engineer IV

Premera Blue Cross•Mountlake Terrace, WA

31d•Hybrid

About The Position

Our purpose, to improve customers’ lives by making healthcare work better, is far from ordinary. And so are our employees. Working at Premera means you have the opportunity to drive real change by transforming healthcare. Premera is committed to being a workplace where people feel empowered to grow, innovate, and lead with purpose. By investing in our employees and fostering a culture of collaboration and continuous development, we’re able to better serve our customers. It’s this commitment that has earned us recognition as one of the best companies to work for. Learn more about our recent awards and recognitions as a greatest workplace. Learn how Premera supports our members, customers and the communities that we serve through our Healthsource blog: https://healthsource.premera.com/. 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 help shape AI strategy, guide solution design, and lead the delivery of high‑impact capabilities across data pipelines, model development, and AI‑enabled services. This role blends deep hands‑on engineering with leadership: you’ll drive prototypes into production, influence architecture decisions for multi‑faceted AI systems, mentor other engineers, and elevate best practices for responsible AI in a highly regulated environment. This is a hybrid role, located on our campus in Mountlake Terrace, Washington.

Requirements

Bachelor’s degree in computer science, Information Systems, Statistics, Mathematics, or a related field, or equivalent experience.
At a minimum, combined expertise of 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.

Nice To Haves

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 productionizing AI models, including scalable pipelines and robust monitoring systems.
Strong background developing deep learning models using modern frameworks (e.g., TensorFlow, 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.
Knowledge, Skills, and Abilities 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 skills and the ability to build secure, stable systems at scale.
Expertise in AI system design and deployment patterns (pipelines, low‑latency services, monitoring).
Strong communication and stakeholder influence—able to explain technical tradeoffs clearly to non‑technical audiences.
Mentorship and leadership mindset with a commitment to knowledge sharing and raising team capability.

Responsibilities

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.

Benefits

Medical, vision, and dental coverage with low employee premiums.
Voluntary benefit offerings, including pet insurance for paw parents.
Life and disability insurance.
Retirement programs, including a 401K employer match and, believe it or not, a pension plan that is vested after 3 years of service.
Wellness incentives with a wide range of mental well-being resources for you and your dependents, including counseling services, stress management programs, and mindfulness programs, just to name a few.
Generous paid time off to reenergize.
Looking for continuing education? We have tuition assistance for both undergraduate and graduate degrees.
Employee recognition program to celebrate anniversaries, team accomplishments, and more.
For our hybrid employees, our on-campus model provides flexibility to create your own routine with access to on-site resources, networking opportunities, and team engagement.
Commuter perks make your trip to work less impactful on the environment and your wallet.
Free convenient on-site parking.
Subsidized on-campus cafes make lunchtime connections with colleagues fun and affordable.
Participate in engaging on-site activities such as health and wellness events, coffee connects, disaster preparedness fairs and more.
Our complementary fitness & well-being center offers both in-person and virtual workouts and nutritional counseling.
Need a brain break? Challenge someone to a game of shuffleboard or ping pong while on campus.