Design, build, and maintain the systems that measure and improve the quality of Bask Health's AI-powered applications, focusing on evaluation infrastructure, automated testing, and production reliability.
Responsibilities
Design and build evaluation infrastructure for AI and machine learning applications across Bask Health.
Develop automated testing systems for large language model applications and intelligent workflows.
Establish measurable quality standards for production AI features.
Create evaluation pipelines that assess accuracy, relevance, completeness, consistency, and reliability.
Build and maintain representative datasets for testing AI application behavior.
The Lead AI Engineer is responsible for architecting, developing, deploying, and supporting enterprise-scale Agentic AI solutions using LLMs, RAG pipelines, model orchestration frameworks, Agentic frameworks, and secure API solutions to automate business processes and enhance decision-making.
Compensation
Salary Range:
$121,350.00 - $199,365.00
The salary range reflected above is a good faith estimate of base pay for the primary location of the position. The salary for this position ultimately will be determined based on the education, experience, knowledge, and abilities of the successful candidate. In addition to salary, this role may also be eligible for annual, sales, or other incentive compensation.
Responsibilities
Implement and test complex code changes for specific requirements, applications, and standalone programs.
Integrate product features with awareness of product design, market trends, production adoption, and competition.
Define, influence, and track metrics that measure solution success and adoption.
Lead delivery of high-quality solutions and identify opportunities for multiple products to work together to create customer value.
Lead solution design and implementation for projects spanning multiple teams and influence the software engineering roadmap.
Lead the end-to-end development, implementation, and life‑cycle governance of global policies targeting scaled adversarial abuse, generative AI exploitation, coordinated spam networks, and inorganic platform manipulation.
Analyze malicious actor strategies, incentives, and evasion techniques to develop policy architectures that mitigate widespread abuse.
Partner directly with Engineering, Data Science, and Product Management to translate nuanced policy principles into machine‑enforceable heuristics and automated enforcement workflows.
Serve as the subject matter expert on adversarial abuse, briefing cross‑functional executives, Legal counsel, Public Policy, and others on emerging threat vectors, high‑profile investigations, and long‑term ecosystem defense.
Develop and maintain machine learning and forecasting solutions for store, warehouse, and ATM systems.
Compensation
Year End Bonus: one month’s extra pay (pro-rated in the first year) each year if associate remains employed through issue date of the bonus check that year.
Responsibilities
Develop and maintain machine learning and forecasting solutions using Python and SQL
Build scalable ML and data pipelines using Databricks, Spark/PySpark, and Delta Lake
Develop automated deployment processes using Databricks Asset Bundles (DABs) and CI/CD
Partner with data scientists, cloud engineers, and business teams to produce demand forecasting models
Monitor model and pipeline performance and troubleshoot production issues
Requirements
Bachelor’s degree in computer science or another analytical discipline, or equivalent experience
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