Senior Director, Cloud and AI Platforms

Date Posted: 2026-03-21 Country: United States of America Location: OT999: 1CP - Farmington, CT One Carrier Place, Farmington, CT, 06032 USA Would you like to join a truly international, talent driven company that values Safety, Ethics, Quality, Innovation and Employee Opportunity? The Senior Director, Cloud and AI Platforms lead the strategy, architecture, and enablement of the enterprise cloud and AI platform ecosystem. This role partners across product, security, data, and application teams to deliver secure, reliable, scalable cloud capabilities (compute, storage, network, Kubernetes, CI/CD, observability, developer experience) and AI platform capabilities that accelerate delivery and improve business outcomes. This person must be able to go into the office in Farmington, CT three times a week. On a typical day you will: Set and communicate the vision, operating model, and multi-year roadmap for Multi cloud & AI Platforms aligned to enterprise strategy. Lead cloud architecture team delivering the foundation for core cloud services (landing zones, identity, networking, compute, storage, Kubernetes, service mesh) with architectures designed to meet SLOs and reliability practices. Own the developer enablement strategy, including CI/CD patterns, infrastructure-as-code, golden paths, templates, and self-service automation. Establish scalable observability and DR architecture: monitoring, logging, tracing, and disaster recovery tools & design. Define and evolve the enterprise AI platform architecture, including AI landing zones, model serving patterns, RAG architectures, vector search integration, prompt management, evaluation, and guardrails. Define GenAIOps standards including reproducibility, automated testing, model/prompt evaluation, and release governance. Partner with Security, Risk, and Compliance to embed security-by-design, policy-as-code, data protection, and responsible AI controls (privacy, fairness, explainability, auditability). Drive cloud financial management (FinOps): cost visibility, unit economics, budgeting, chargeback/showback, optimization, and vendor management. Define platform standards and reference architectures, influence application modernization and AI adoption across business units. Manage and develop leaders: hiring, performance management, coaching, succession planning, and creating a high-trust, high-accountability culture. Measure and improve platform outcomes using KPIs (deployment frequency, lead time, change failure rate, MTTR, SLO attainment, cost per workload, AI time-to-value). Represent the platform organization in executive forums; provide clear updates on progress, risks, and tradeoffs. What you will need to be successful: 12+ years of experience in cloud architecture, platform engineering, infrastructure modernization, or containerization, with a strong foundation in related technologies. Includes at least 5+ years leading managers and multi-team organizations Proven experience building and operating enterprise cloud platforms (AWS, Azure, and/or GCP) at scale, including networking, security, and governance Deep knowledge of Kubernetes and container platforms; infrastructure-as-code (Terraform, Bicep/ARM, CloudFormation), and modern CI/CD practices Track record delivering high-availability systems with mature incident management, SLO/SLI practices, and strong operational rigor Hands-on understanding of AI/ML and generative AI platform needs (model lifecycle, serving, evaluation, vector databases, RAG architectures, AI cost management) Experience implementing security-by-design and compliance controls in regulated environments (e.g., SOC2, ISO 27001, PCI, HIPAA—as applicable) Strong executive communication skills with ability to translate technical tradeoffs into business impact Bachelor’s degree in computer science, Engineering, or equivalent practical experience Preferred Qualifications Experience establishing an internal developer platform (IDP) and product management mindset for platform teams Experience with enterprise IAM patterns, zero trust architectures, secrets management, and policy-as-code (e.g., OPA/Gatekeeper) Experience with data platforms and governance (lakehouse/warehouse, data catalog, lineage) and their integration with AI/ML workflows Familiarity with major AI platforms and tooling (e.g., Azure AI, SageMaker, Vertex AI, Databricks, Snowflake, OpenAI/Azure OpenAI) and evaluation/guardrail frameworks Master’s degree (MS/PhD) in a relevant field or MBA with strong technical background Leadership Competencies Str