Director – AI & Automation

Das ist der Job

Regularly communicate AI and automation strategy, progress, and ROI to senior executives and governance bodies.

Darum lohnt es sich

Lead and develop a high‑performing AI & Automation Engineering team. Build, lead, and retain a diverse team of AI/ML engineers, automation engineers, and related roles, setting clear goals, expectations, and development plans.

Demonstrated experience leading and scaling multi‑disciplinary engineering teams, including hiring, performance management, and career development.

Responsibilities Define and maintain a multi‑year AI and automation roadmap that supports strategic goals in Stars, risk adjustment, payment accuracy, prior authorization, clinical quality, and member experience.

Partner with C‑suite and senior leaders to identify and prioritize high‑ROI use cases where AI and intelligent automation create durable competitive advantage. Collaborate with Product, Data Engineering, Clinical Operations, Finance, Compliance, and Security to translate business requirements into technical solutions and track realized value.

Work with Legal, Compliance, and Privacy to ensure all AI and automation solutions meet CMS, HIPAA, and internal governance standards. Own the operating budget for AI & Automation Engineering, including cloud spend, third‑party platforms, and external partners.

Fulfill supervisory responsibilities in accordance with organization policies and applicable laws, including interviewing, hiring, training, and appraising performance. Requirements 8–12 years of progressive experience in software engineering, data science, or AI/ML roles. At least 3–5 years in a senior leadership or director‑level position.

Proven track record of delivering production‑grade AI/ML systems and large‑scale automation solutions in a regulated or enterprise environment. Deep expertise in machine learning, NLP, generative AI (LLMs, RAG pipelines), agentic frameworks, and intelligent process automation (RPA and orchestration).

Experience managing budgets, vendor relationships, and technology platform decisions at a department or function level. Bachelor's degree in Computer Science, Computer & Electrical Engineering, Mathematics, Data Science, or a related quantitative field (or equivalent experience).

Demonstrated senior‑level proficiency with AI/ML engineering practices, cloud platforms, and enterprise automation through professional experience. Working knowledge of cloud AI/ML governance and platform management (AWS, Azure, or GCP) at a leadership level; certification or equivalent experience accepted.

Preferred: Experience in healthcare — specifically Medicare Advantage, managed care, or payer environments. Preferred: Knowledge of healthcare data standards including HL7 FHIR, ICD‑10/CPT, or DICOM as applied to AI systems.

Preferred: Published research, conference presentations, or demonstrated thought leadership in AI/ML or enterprise automation. #J-18808-Ljbffr