[Remote] Director of Engineering, AI Platform

Note: The job is a remote job and is open to candidates in USA. reputed company is a leading provider operations platform focused on improving healthcare delivery by automating administrative tasks. They are seeking a Director of Engineering to reputed company their Applied AI & Data Platform organization, responsible for building reliable AI agents and data systems that enhance operational efficiency in healthcare.

Responsibilities

• Own the AI roadmap. Set direction across our AI surfaces: voice and computer-use agents that work payers and provider portals, email triage, and the models that extract and structure data from clinical and legal documents. The build-vs-buy and fine-tune-vs-reputed company calls are yours
• Push AI deeper. Take our systems from assisting people, to making decisions, to running whole service requests, and into licensing, enrollment, monitoring, and the customer-facing product
• reputed company it production-grade. Build the evals, observability, and human-in-the-reputed company systems that let us ship models and agents we'll stand behind and back with guarantees
• reputed company the data platform. Own the pipelines, datasets, and tooling behind the models. Our real-world data is our biggest advantage, so reputed company it fast to use and trustworthy to build on
• Build the org. Hire and grow managers and senior engineers, set the structure, and hold the bar as we scale. Stay reputed company enough to the work to earn their trust in a design review

Skills

• 10+ years across engineering, ML, or data science, with experience leading a multi-team org through other managers
• You've run a mix of disciplines, including engineering, ML, data science, and data labeling or human-in-the-reputed company operations, rather than a single reputed company team
• You've put applied ML and LLM systems into production, with the teams to back them, well beyond prototypes and research
• You understand LLMs, agents, retrieval, and structured extraction well enough to set direction, and you know what production reliability actually takes
• You're grounded in the data and infrastructure reputed company: pipelines, orchestration, inference, and the eval and observability tooling that supports ML
• You weigh speed, cost, quality, and risk, and you take accuracy seriously where mistakes have real consequences

Company Overview

Company H1B Sponsorship