Build and scale reusable AI capabilities across the enterprise, including Evaluation-as-a-Service (EaaS) and Document Intelligence pipelines
Define the technical foundation for reliable, governed, and scalable AI systems
Operate at the intersection of AI engineering, platform development, and responsible AI governance
Collaborate with a multi-disciplinary team of clinicians, engineers, and researchers to deliver an end-to-end product
Design and build reusable AI platform capabilities that enable scalable model development
Develop and operationalize robust pipelines for experimentation, benchmarking, and model comparison
Define and standardize schemas, APIs, and workflows
Improve reliability, reproducibility, and quality through structured experimentation
Partner with cross-functional teams (engineering, data science, product)

Bachelor's degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.) or equivalent degree and 6 or more years of experience
Experience with Python, APIs and distributed systems
Experience with ML/LLM pipelines and evaluation techniques preferred
Experience productionizing AI systems (monitoring, logging, scaling) preferred
Experience designing reusable frameworks or platform capabilities
Familiarity with Responsible AI, model evaluation, and governance practices

Senior AI Engineer

Key skills