responsible for the engineering work necessary for successful creation, deployment and managing of AI capabilities of the Intelligent Delivery Platform
ensuring data quality
creation of new data pipelines
optimization and management of existing data pipelines
ingestion and curation of data sources for Gen AI purposes (including chunking/embedding strategies for RAG system)
AI Agent delivery
Prompt Engineering
selection and configuration of AI-specific tools and platforms
management and monitoring of AI models through MLOps tools and model ops practices
operationalizing AI capabilities, working closely with larger team who will supplement where traditional application development support is needed
Requirements
Bachelor degree and 5 years of work experience in a computer science, engineering, or related field OR Master’s degree and 4 years of work experience in a computer science, engineering, or related field OR Ph.D. and 2 years of work experience in a computer science, engineering, or related field
Learning and growth mindset
Customer-focused
Interpersonal, verbal and written communication skills
Must demonstrate proficiency in at least five and mastery in one of the following six areas: data analysis and relational-style query languages; data pipelining and ETL; working with semi structured and unstructured data; a high
level programming language; distributed computing; understanding of healthcare
Proficiency in iterative development practices
Independently delivering or leading the delivery of data engineering solutions for multiple complex analytics or data science projects and products
A track record of independently delivering or leading the delivery of ML engineering capabilities
Experience in Python-based Data Science frameworks (LangChain, LangGraph, LangFuse)
Experience in Model evaluation and deployment
Experience in data curation, prep, training, and fine-tuning of Models