A Career of Your Calling

The Impact You Will Have

Blue Cross Blue Shield of Minnesota is hiring a Senior AI Engineer to help design, deploy, and operationalize AI and machine learning solutions that improve data science productivity and reduce operational overhead. In this role, you will work handson withdata scientists, analytics teams, and business partners to translate models and analytical workflows into reliable, scalable, productionready systems.

You will focus on automating data pipelines and AI/ML workflows, strengtheningcloudbaseddeployment patterns, and improving the efficiency, reliability, and quality of AI solutions in production. You will bring strong execution, collaboration, and technical depth to your work whileoperatingwithin established architectural standards and partnering closely with senior technical leaders.

The ideal candidate is a hands-onSeniorlevel AI Engineer with experience building, deploying, and supporting ML models in production environments. You bring 3+ years ofhandsonexperience with generative AI, large language models, NLP, or related technologies, along with strongproficiencyin Python or similar languages and modern ML frameworks such asPyTorchor TensorFlow. You have experience deploying AI solutions in cloud environments such as AWS, Azure, or GCP using establishedMLOps, CI/CD, containerization, and monitoring practices. You approach AI systems with a strong focus on reliability, scalability, and integration with existing platforms while adhering to security, governance, and quality standards.Strong communicationskills,cross functionalcollaboration, and an interest in mentoring or supporting other engineers are important, with experience in regulated environments such as healthcare preferred.

Your Responsibilities 

• Deploy artificial intelligence (AI) and machine learning (ML) models in production, working with data scientists and other stakeholders in the organization.

• Work with a team of data scientists and AI engineers to ensure seamless AI development,integrationand deployment in production.

• Collaborate with cross-functional teams to understand the analytical and ML needs and provide technical solutions.

• Mentor and help junior data scientists to train and run models in cloudenvironmentlike AWS and Azure and automation of data science processes.

• Develop andmaintainunit tests, integration tests, and end-to-end tests for APIs and ML models. 

• Evaluate, implement emergingtoolsand cloud services for analytics data engineering to improve productivity of the team.

• Work with a multidisciplinary team to build high quality data pipelines that will be used by data scientists and business analysts to generate insights

Required Skills and Experience

• 5+ years ofrelated professionalexperience. All relevant experience including work, education, transferable skills, and military experience will be considered.

• 3+ years of experience as a data engineer or similar role. Experience with ML engineering or datascience,data analytics,software engineering.

• Proficient programming skills in languages like Python, Scala, etc.

• Proficient experience with Machine Learning model deployment in production.

• Proficient experience with cloud platforms like AWS, Azure, etc.

• Proficiencyin data pipeline orchestration tools such as Apache Airflow, Docker, Kubernetes, etc.

• Proficient experience with SQL and cloud databases like Redshift, Athena, AWS services like Glue, etc.

• Proficient experience implementing, testing, and fielding automation for AI and ML solutions.

• Excellent communication, collaboration, and presentation skills.

• High school diploma (or equivalency) and legal authorization to work in the U.S.

Preferred Skills and Experience

• Bachelor's or master’sdegree in computer science, data Science, or a related field.

• Experience with developing and deploying Large Language Models, Retrieval Augmented Generation (RAG), GenerativeAI technologies.

• Experience with ML frameworks, includingKeras, Pandas, TensorFlow,Pytorch, etc.

• Proficient experience using AWS technologies for Machine Learning – SageMaker, S3, etc.

• Experience with software engineering concepts, including version control and unit testing.

• Experience using visualization tools such asPowerBI, Tableau, Looker, etc. 

• Certification in relevant technologies.