Engineering Manager, Case Strategy

Role overview Lead the engineering function that turns data, models, and machine-learning capabilities into smarter decisions across a healthcare reimbursement dispute workflow. The position combines people leadership with hands-on technical direction, owning the systems that apply case strategy throughout the Independent Dispute Resolution process and directly tying engineering outcomes to customer value and recurring revenue.

Responsibilities - Drive engineering outcomes that improve reimbursement results for customers, connecting the technical roadmap to measurable gains in customer value and annual recurring revenue. - Own the data models, databases, APIs, services, and full-stack workflows that operationalize case strategies across the dispute lifecycle. - Partner closely with data-science and applied-science teams to move AI and machine-learning capabilities from experimentation into reliable, production product features. - Build the data and feedback flywheel that captures outcomes, surfaces useful signals, and feeds real-world results back into model development. - Lead, coach, and grow an experienced engineering team; set priorities, create accountability, and preserve rigorous technical debate. - Shape the technical direction across Python services, GCP infrastructure, data systems, LLM-enabled capabilities, and customer-facing applications, using AI-enabled development tools to prototype and contribute when useful.

Requirements - Several years building and leading engineering teams in early-stage environments, including 7+ years as an individual contributor and 2+ years as a manager. - Strong individual-contributor foundation with the technical depth to guide architecture, evaluate tradeoffs, and earn the trust of senior engineers. - Experience delivering production AI or machine-learning products, or managing engineering work in close partnership with data-science teams. - Familiarity with building reliable systems around models, including data pipelines, feedback loops, APIs, monitoring, and product workflows. - Ability to lead through ambiguity and imperfect data, forming clear points of view without waiting for every question to be resolved. - Skill in managing experienced, opinionated engineers, bringing clarity and decision-making without shutting down productive disagreement. - Track record of connecting engineering work to business and customer outcomes, with comfort owning results tied to revenue.

Nice to have - Background in healthcare, provider reimbursement, revenue-cycle management, claims, or Independent Dispute Resolution. - Experience with optimization, experimentation, decision systems, strategy models, or feedback-driven machine-learning products. - Hands-on experience scaling an early engineering team or building production AI systems using Python, GCP, and large language models.

Benefits and work setup - Competitive compensation including equity. - Full health, dental, and vision coverage. - 401(k) retirement savings plan. - Flexible time off and company-wide connection events. - Hiring concentrated around Los Angeles and New York hubs, with remote or hybrid flexibility considered by role and team.