Description:
As a Solution Architect/AI Engineer V, you'll embody thought leadership, make commitments, and lead staff, executives, and external stakeholders to solve complex business issues and systems. Operating independently with minimal direction, you'll navigate AI/ML solutions from concept to full production. Your visionary approach will drive ideation and prototyping of new AI products, utilizing sophisticated tools and technologies. Leading the enterprise in developing and deploying ML algorithms, you'll ensure a robust AI infrastructure, fostering continuous learning and innovation across cross-functional teams, propelling the organization to new heights in the AI/ML domain.
This is a hybrid role on our Mountlake Terrace campus.
What you’ll do:
- Design and ensure the development of comprehensive systems and frameworks for AI applications and products.
- Pitch concepts to leaders on all levels of the organization as well as externally, and then lead construction of prototypes and minimum viable products to validate AI/ML solutions before committing substantial resources.
- Lead the design and implementation of complex multi-cloud architectures that power sophisticated AI systems.
- Create the underlying data pipeline architectures feeding, logging, and training complex AI systems.
- Develop specifications for low latency APIs and services necessary to deploy AI models and incorporate them into applications.
- Design the oversight plans and processes for managing deployed models and AI systems.
- Foster within the team principled, agile-like development practices.
- Develop team-wide documentation practices that will ensure adherence to corporate policies and expectations. Apply those standards to ensure thorough and maintained documentation for all work products.
- Develop and ensure peer review standards and procedures for all work within the team.
- Ensure AI engineers follow AI/ML and industry best practices and methodologies.
- Keep abreast of new tools and concepts through reading, documentation, or literature and actively practice skills development.
- Advise senior leadership and executives on matters such as enterprise AI strategies, AI related technology strategies and roadmaps, AI related infrastructure strategies, and roadmaps.
- Make AI solution commitments on behalf of Premera to external stakeholders that realize business value and ensure AI governance adherence, AI best practices, and data quality.
- Provide thought leadership internally. Contribute externally to the AI community or the healthcare community at large.
- Support or guide technical direction of project initiatives, collaborating with the rest of the design team and stakeholders ensuring that development milestones and deadlines are met. Provide feedback and advice on peer designs in an open and collaborative environment, mentor other engineering staff, and act as technical and business leader sharing knowledge and expertise with others inside team as well as with other stakeholders. Proactively contribute to knowledge sharing across Premera developer community.
- Influence change and evolution in IT standards, practices, and processes, and drive application of engineering best practices for your team.
- Stay current in industry trends and contribute to expanding the knowledge and skills of peers and teammates while researching and gaining understanding of innovative technology solutions and identifying their application to the organization’s business. Actively mentor individuals and teams and participate in internal and external opportunities to increase knowledge on advanced technical issues; help managers guide career growth of their team members; research and benchmark our technology against competing systems in the industry.
What you’ll bring:
Minimum Qualifications
- Bachelor's Degree in Computer Science, Statistics, Mathematics, or a related field; or 2+ years of experience in a related, professional IT/analytics position.
- Minimum of 5 years of industry experience in developing, deploying, and maintaining AI or ML systems. Up to two years of industry experience may be substituted with an AI centered Master’s/Ph.D. or AI Engineering certifications.