Lead Director – Artificial Intelligence, Machine Learning, Data Engineering

Emploi pas sur LinkedIn

🕒 il y a 28 jours

🦌 Connecticut – Distant

🦌 Connecticut – Remote

💵 $144 200 - $288 400 / an

⏰ Temps Plein

🟠 Senior

🚰 Ingénieur Data

Postuler Maintenant

Trouver des Emplois à Distance Similaires

Configurer une alerte email pour les nouveaux emplois

📊 Vérifiez votre score de CV pour ce poste

Améliorez vos chances d'obtenir un entretien en vérifiant votre score de CV avant de postuler.

Télécharger le CV

CVS Health

Site WebLinkedInTous les Emplois

10 000+ employés

Fondée en 1963

🏥 Santé

⚕️ Assurance santé

🛒 Commerce de détail

Healthcare • Healthcare Insurance • Retail

CVS Health est une entreprise américaine de premier plan dans le domaine de la santé, dédiée à l'amélioration de l'accès et de l'accessibilité financière des soins de santé. L'entreprise s'appuie sur une approche globale qui comprend les services de santé, l'assurance santé et la gestion des prestations pharmaceutiques. À travers ses filiales, telles qu'Aetna et CVS Caremark, CVS Health propose une gamme de services qui favorisent le bien-être, la gestion des maladies chroniques et une couverture abordable des médicaments prescrits. CVS Health exploite des pharmacies de proximité, fournit des services de pharmacie par correspondance et gère des programmes de médicaments spécialisés, visant à rendre les soins de santé pratiques et accessibles à tous. Animée par une mission de connecter les individus aux services de soins essentiels, CVS Health s'engage à favoriser des communautés en meilleure santé et à soutenir le bien-être de toutes les personnes.

Description

• Lead the strategy, architecture, and delivery of enterprise AI platform capabilities, including RAG, GraphRAG, vector search, MCP servers, memory and context services, reusable agents, model lifecycle management, and developer enablement accelerators that drive scalable AI/ML adoption. • Lead the strategy, development, and operation of reusable data products and enterprise data engineering capabilities, including data ingestion, transformation, quality, metadata management, lineage, feature engineering, and data services that support AI, analytics, and business outcomes. • Establish enterprise standards and operational practices for platform reliability, observability, infrastructure automation, security, privacy, compliance, model governance, responsible AI, risk management, disaster recovery, capacity planning, and audit readiness. • Partner with Architecture, Cybersecurity, Infrastructure, Product, Data, and Business leaders to guide technology strategy, evaluate emerging technologies, define enterprise standards, optimize investments, reduce duplication, and accelerate AI and data modernization initiatives. • Build, lead, and develop high-performing teams of Engineering Managers, Data Engineers, AI Engineers, Platform Engineers, and Operations Engineers while fostering a culture of innovation, accountability, continuous learning, inclusion, operational excellence, and measurable business impact.

🎯 Exigences

• 10+ years of experience in software engineering, data engineering, artificial intelligence, machine learning, platform engineering, or related engineering disciplines, including designing and delivering enterprise-scale technology solutions. • 7+ years of experience building and leading large-scale platform engineering organizations responsible for enterprise AI/ML platforms, data platforms, products, and technology delivery. • 7+ years of hands-on experience building and scaling AI/ML platforms, DevSecOps, MLOps, LLMOps, deployment automation, security engineering, and platform operations supporting mission-critical workloads. • 7+ years of experience designing and operating secure cloud-native platforms within highly regulated environments, including privacy, security, governance, compliance, identity management, audit controls, risk management, and operational resilience. • 5+ years of experience leading and developing high-performing engineering organizations, including Engineering Managers and senior technical professionals, while building enterprise Data Engineering capabilities, including large-scale data ingestion, batch and streaming architectures, data governance, and reusable data products.

🏖️ Avantages

• medical • dental • vision coverage • paid time off • retirement savings options • wellness programs and other resources, based on eligibility.