build and scale reusable AI capabilities across the enterprise
define the technical foundation for reliable, governed, and scalable AI systems
operate at the intersection of AI engineering, platform development, and responsible AI governance
recommend solutions to new and complex problems
collaborate with a multi-disciplinary team of clinicians, engineers, and researchers
design and build reusable AI platform capabilities
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 to translate use cases into production-ready, reusable capabilities
optimize AI systems for performance, scalability, and cost efficiency
embed Responsible AI principles by implementing governance, evaluation standards, and audit-ready processes

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 with productionizing AI systems (monitoring, logging, scaling) preferred
Experience designing reusable frameworks or platform capabilities
Familiarity with Responsible AI, model evaluation, and governance practices
Knowledge of: Document Intelligence (OCR, NLP, structured extraction)
Exposure to platform engineering and familiarity with modern AI workflows and multi model systems preferred.

Senior AI Engineer

Key skills