Lead Director – Artificial Intelligence Solutions Engineering, Delivery
Connecticut, United States of America
Full Time
1 hour ago
$144,200 - $288,400 USD
No H1B
Key skills
AWSAzureCloudCyber SecurityGoogle Cloud PlatformAIArtificial IntelligenceMachine LearningLarge Language ModelsRAGAgenticAmazon Web ServicesGCPGoogle CloudResource PlanningProduct Management
About this role
Role Overview
Lead the end-to-end delivery of enterprise Artificial Intelligence and Machine Learning products, from opportunity identification and solution design through proof of concept, production deployment, enterprise adoption, and value realization, while delivering measurable business outcomes aligned to strategic objectives.
Define and operationalize solution engineering, architecture, and delivery standards for AI-enabled products, establishing scalable, secure, resilient, and reusable implementation patterns aligned with enterprise technology standards, governance requirements, and engineering best practices.
Partner with Product, Architecture, Cybersecurity, Infrastructure, Observability, Data, and Business leaders to identify high-value use cases, prioritize investments, define success metrics, and accelerate adoption of Artificial Intelligence capabilities across the enterprise.
Manage technology investments, strategic portfolios, budgets, vendor relationships, resource planning, and governance processes, providing executive visibility into delivery performance, business value, risks, dependencies, financial outcomes, and operational readiness.
Build, lead, and develop high-performing teams of Technical Product Managers, Solutions Engineers, and Forward Deployment Engineers while fostering a culture of innovation, accountability, operational excellence, continuous learning, inclusion, and customer-focused delivery.
Requirements
10+ years of experience developing enterprise software products and platforms utilizing Artificial Intelligence, Machine Learning, and modern software engineering practices.
10+ years of experience delivering enterprise-scale technology solutions within complex, highly regulated environments.
10+ years of experience designing, implementing, and operating cloud-native solutions across Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP) environments.
7+ years of experience building, leading, and scaling product management, software engineering, or solutions engineering organizations responsible for enterprise technology delivery and transformation.
5+ years of experience building and deploying Artificial Intelligence and Machine Learning solutions utilizing Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), GraphRAG, agentic architectures, observability, model monitoring, and production AI operational practices.