Premera Blue Cross
Improve customers' lives by making healthcare work better.
AI Engineer – IV
Location
Alaska + 26 moreAll locations: Alaska, Arizona, California, Colorado, Florida, Idaho, Iowa, Kansas, Kentucky, Maine, Montana, Nevada, New Hampshire, New Mexico, North Carolina, Oklahoma, Oregon, Michigan, Minnesota, Missouri, South Carolina, South Dakota, Tennessee, Texas, Utah, Washington, Wisconsin
Posted
50 days ago
Salary
$131.9K - $237.4K / year
Bachelor Degree5 yrs expExperience acceptedEnglishAzureCloudKubernetes
Job Description
• Recommend and develop comprehensive multi-agent systems and enterprise AI systems for complex applications and products.
• Pitch concepts to team leadership and lead construction of prototypes and minimum viable products to validate AI/ML solutions before committing substantial resources.
• Assist in designing and implementing the cloud architecture of large multi-faceted AI systems on Kubernetes using platforms like Azure AI Foundry with comprehensive agent governance.
• Assist in the design and scaffolding of robust data pipelines that drive large complex AI systems including graph databases, tensor-based fusion, and multi-model retrieval.
• Develop specifications for enterprise-wide agent communication standards, tool governance, and evaluation harnesses to deploy AI models at scale.
• Develop the code for monitoring models and AI systems including customer evaluation metrics, agent behavior analytics, and comprehensive drift detection that ensures consistent and reliable performance.
• Actively participate in a team that exercises principled, agile-like development practices.
• Create and maintain thorough documentation that is consistent with team procedures, corporate policies, and expectations including architectural decision records.
• Ensure peer review on all assigned work, as well as conduct peer reviews over the work of others as requested.
• Guide and mentor junior AI engineers on AI/ML and industry best practices and methodologies and emerging standards like A2A, MCP, and novel reasoning/retrieval techniques.
• Keep abreast of new tools and concepts through reading documentation or literature and actively practicing skills development.
• Advise team and division leadership on matters such as enterprise AI strategies, AI related technology strategies and roadmaps, AI related infrastructure strategies, and roadmaps.
• Meet and collaborate with external stakeholders to conceptualize AI solutions that realize business value while ensuring AI governance adherence, AI best practices, and data quality.
• Provide thought leadership to the Premera AI community.
Job Requirements
- 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/PhD degree or AI Engineering certifications.
- At least 4 years of experience in developing enterprise scale multi-agent systems using advanced orchestration and evaluation frameworks.
- Previous experience with novel fusion techniques (TRF, learned rankers) and production GraphRAG at scale.
- Experience implementing enterprise AI systems with comprehensive governance, security, and compliance features.
- Publications, patents, or significant open-source contributions in agent architectures or advanced retrieval systems.
- Minimum of 4 years of experience in successfully productionizing AI models, including constructing scalable data pipelines and establishing robust monitoring systems.
- At least 5 years working within agile-like teams and environments.
- Mastery of complex multi-agent architectures including distributed orchestration.
- Expert knowledge of advanced fusion methods (TRF, tensor-based ranking).
- Ability to design enterprise-scale RAG systems with comprehensive governance.
- Deep expertise in agent evaluation and benchmarking methodologies.
- Proficiency in implementing agent safety systems and attack mitigation.
- Advanced knowledge of graph-augmented retrieval and ontology alignment.
- Experience with multi-modal agent systems and embeddings.
- Ability to design agent communication standards and protocols.
- Expertise in token optimization and cost management at scale.
- Knowledge of agent pool management and scale-to-zero architectures.
- Experience with agent simulation and testing frameworks.
- Ability to mentor teams on cutting-edge AI engineering practices.
- Understanding of regulatory compliance for agentic AI systems.
- Ability to articulate the technical details and tradeoffs of AI solutions to non-technical stakeholders in a clear and concise manner.
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 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.
- Generous paid time off to reenergize.
- Tuition assistance for both undergraduate and graduate degrees.
- Employee recognition program to celebrate anniversaries, team accomplishments, and more.
- On-campus model provides flexibility with access to on-site resources, networking opportunities, and team engagement.
- Commuter perks to lessen environmental and financial impact.
- Free convenient on-site parking.
- Subsidized on-campus cafes for affordable lunches.
- Engaging on-site activities such as health and wellness events, coffee connects, disaster preparedness fairs.
- Complementary fitness & well-being center with both in-person and virtual workouts and nutritional counseling.
- Fun recreational activities on campus like shuffleboard or ping pong.
