Lead AI Engineer

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Job Description: ​

Position Summary: 

As a Lead AI Engineer at agilon health, you will deliver production-grade AI products within agilon’s Tech Group. Key areas of development include prioritization models, unstructured data processing, clinical suspect identification, and clinical risk models. In this role, you will develop and deploy AI products with clinical LLMs, NLP, and standard ML tools. You will work closely with stakeholders across the organization to understand the clinical, business, and technical requirements, and be responsible for the impact that AI products create at agilon.  

Essential Job Functions: 

• Leverage agilon’s unstructured clinical data, including notes and images, with NLP and LLM tools.  

• Create production-grade AI products, including the supporting data pipelines, monitoring, and performance analysis. 

• Communicate the value and opportunities of AI to internal stakeholders.  

• Collaborate with Insights Engineering, Clinical Analytics, and Centralized Operations teams to drive real-world outcomes.  

• Contribute to the development of our AI products in a fast-paced, agile environment. 

Required Qualifications:  

Minimum Experience 

• 7+ Years of experience in a related field, including Analytics, Data Science, or Data Engineering.  

• 3+ Years in a healthcare setting, preferably value-based care.  

Education/Licensure 

• Bachelor’s and/or master’s in a quantitative field, such as Computer Science, Data Science, or Mathematics. 

Knowledge, Skills, and Abilities: 

• Expertise in Python programming and ML libraries and practices (e.g., scikit-learn, pandas).  

• Strong SQL skills and experience (prefer Snowflake + dbt) with data visualization tools (prefer Sigma).   

• Experience with cloud data engineering and ML infrastructure tools, such as AWS Sagemaker, Airflow, dbt,  etc.  

• Deep knowledge of statistical analysis and predictive modeling techniques, particularly those used in a healthcare setting.  

• Understanding of value-based care concepts in the US, including Medicare payment models, medical claims data, and electronic health records.  

• Intellectual curiosity and a passion for using data to solve real-world problems at scale.  

• Excellent communication skills and the ability to proactively explain complex concepts to non-technical stakeholders.  

• Enthusiasm for learning and adapting in a dynamic startup environment. 

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Pay Range: ​

Salary range shown is a guideline. Individual compensation packages can vary based on factors unique to each candidate, such as skill set, experience, and qualifications.