Solution Architect/ai Engineer IV

Premera Blue Cross · Insurance · Mountlake Terrace, WA

Solution Architect/AI Engineer IV at Premera Blue Cross, a healthcare company. This hybrid role focuses on designing, developing, and implementing AI solutions, including chatbot interfaces and backend services. Responsibilities include leading prototype construction, designing cloud architecture for AI systems, developing low latency APIs for AI model deployment, and creating code for monitoring AI systems. The role requires a Bachelor's degree or equivalent experience, 12+ years in software development, and at least 2 years of AI system development and deployment experience. Preferred qualifications include experience in regulated environments and healthcare, agile teams, API/service technologies, productionizing AI models, automated testing, and ethical AI practices. Skills include RAG, Tree of Thoughts, Multimodal Chain of Thought, prompt engineering, debugging AI systems, hyperparameter tuning, software design patterns, microservices, distributed computing, container orchestration, and secure software systems at scale.

What you'd actually do

  1. Recommend and develop comprehensive systems and frameworks for AI applications and products, powering solutions for Digital Web experiences, strengths in managing additions for chatbot interfaces and backend services that support them, optimized for cost in consumption of tokens.
  2. Lead construction of prototypes and minimum viable products to validate AI solutions before committing substantial resources, expect to iterate fast and deliver such prototypes autonomously.
  3. Assist in designing and implementing the cloud architecture of large multi-faceted AI systems.
  4. Develop specifications for low latency APIs and services necessary to deploy AI models and incorporate them into applications.
  5. Develop the code for monitoring models and AI systems that ensure consistent and reliable performance.

Skills

Required

  • Bachelor’s Degree in Computer Science, Information Systems, Statistics, Mathematics, or related field, or equivalent experience.
  • Minimum of (12) years of experience in software development and launching online customer products, with knowledge of the software development lifecycle and proficiency in multiple programming languages.
  • At least (2) years of industry experience in developing, deploying, and maintaining AI systems.

Nice to have

  • Experience working with cloud solutions in a highly regulated environment.
  • Experience in the healthcare industry is preferred.
  • Experience working within agile-like teams and environments, with exposure to API and service-based technologies.
  • Experience in successfully productionizing AI models, including constructing scalable data pipelines and establishing robust monitoring systems.
  • Experience in using and creating automated test tools and a strong background in developing strategies for load testing AI experiences live in production.
  • Knowledge of ethical AI practices include explainable AI, fairness, and bias mitigation.
  • Expertise in implementing advanced techniques like Retrieval Augmented Generation, Tree of Thoughts, or Multimodal Chain of Thought in prompt engineering projects.
  • Experience in leading prompt engineering teams and conducting code reviews.
  • Proven experience debugging AI systems and enhancing performance through hyperparameter tuning and similar techniques.
  • Knowledgeable about software design patterns, microservices, distributed computing, container orchestration, and other relevant architectures.
  • Adept software engineering skills, as well as skills building secure, stable software systems at scale.
  • Exceptional written and verbal communication skills, with the ability to articulate complex solutions to diverse stakeholders.
  • Strong mentorship and leadership skills, with a commitment to knowledge sharing and professional development.

What the JD emphasized

  • AI systems
  • AI solutions
  • AI applications
  • AI models
  • AI governance adherence
  • AI best practices
  • AI strategies
  • AI related technology strategies
  • ethical AI practices
  • explainable AI
  • fairness
  • bias mitigation
  • prompt engineering
  • AI systems
  • AI experiences

Other signals

  • design and implementation of sophisticated software and AI solutions
  • understanding of both software engineering principles and real-world experience with AI implementation
  • operate in an agile team environment
  • creating prototypes
  • driving innovative solutions from concept to production
  • productionizing AI models
  • constructing scalable data pipelines
  • establishing robust monitoring systems