ARMRA Colostrum - Sr. Director of AI Infrastructure

Remote - ET (Eastern)2mo ago

Remote Director NA Cloud Computing Artificial Intelligence Principal Executive Director Data Governance AWS Reporting Customer Training REST

Requirements

• 8–12+ years in infrastructure engineering, solutions architecture, or a principal/lead technical role, with direct experience building and scaling enterprise-scale integration systems in CPG, consumer brands, or omnichannel retail environments. Candidates with deeper experience will be considered for the Senior Director level. • Strong hands-on experience with AWS (required). Experience architecting and managing cloud-native environments for production API services, not just dev/test workloads. • Deep experience with REST APIs, webhooks, middleware design, and data pipeline architecture. You've connected messy real-world business systems across multiple departments, not just built demos. • Direct experience deploying and managing LLM-powered systems in production (API integrations, prompt management, agentic workflows). You don't need to train models — you need to make them work reliably at scale. • Experience building and maintaining business intelligence infrastructure: data warehousing, unified reporting, and cross-departmental analytics. • Strong understanding of data governance, privacy compliance (CCPA, GDPR), and security best practices for handling customer PII across integrated systems. • Exceptional ability to lead complex technical initiatives with cross-departmental impact, requiring alignment from multiple executive stakeholders. • Ability to translate between business stakeholders and technical execution. You can sit in a room with a VP and a developer and make sure both walk out aligned. • Strong documentation habits. If you build it, you document it. If you change it, you update the docs. • Comfortable working autonomously in a fast-paced, remote environment where priorities shift and you're expected to move without waiting for permission. • Bias toward building and shipping over planning and presenting. We need someone who gets things into production, not someone who makes great slide decks about what could be. • Hands-on experience with LLM APIs and building agentic AI systems in production. • Background in CX platforms, e-commerce infrastructure, or retail technology systems. • Experience with containerization (Docker) and orchestration for deploying AI microservices. • Familiarity with emerging AI integration standards and protocols. • Experience with data warehousing platforms and modern ETL/ELT tools. • Prior experience building internal tools or dashboards for non-technical users.

Responsibilities

• Integration Architecture & Data Foundations • Own and continuously develop the integration architecture connecting ARMRA's core business platforms across e-commerce, retail, marketing, finance, operations, and customer experience into unified, queryable data flows. • Build, maintain, and extend middleware and API integrations that enable AI agents to perform real actions across business functions: modifying orders, managing subscriptions, surfacing inventory, pulling financial data, and automating operational workflows — all gated to appropriate system states with hard fail safeguards. • Assess, enhance, and expand the existing centralized data architecture to ensure it remains optimized for real-time inference, business intelligence, unified reporting, and AI-driven decision-making as business needs evolve. • Establish and enforce enterprise-wide standards for API security, latency, and throughput across all integrated systems. • Own pipeline reliability, monitoring, and documentation. When something breaks, you fix it. When something's fragile, you rebuild it. • Evaluate and recommend new tools, connectors, and platforms based on API capability, data governance requirements, and integration feasibility. • Cloud Infrastructure & Production AI Systems • Architect, deploy, and optimize AWS cloud environments for performance, reliability, cost efficiency, and scalability across the full AI ecosystem. • Deploy and manage production AI systems — primarily LLM API integrations, workflow automation, and agentic AI agents — with appropriate monitoring, guardrails, and escalation paths. • Build and extend agentic AI systems that execute multi-step tasks autonomously across departments with clear boundaries and human handoff protocols. • Own prompt architecture at the infrastructure level: API configuration, system prompt management, version control, and testing frameworks for production AI workflows. • Drive optimization of cloud computing resources and API usage across the entire AI ecosystem to ensure cost efficiency, elasticity, and scalability. • Data Governance & Compliance • Ensure all AI implementations and data integrations comply with ARMRA's privacy policy, data security SOPs, and regulatory requirements (CCPA/CPRA, GDPR where applicable). • Enforce data sovereignty across the enterprise: ARMRA's customer and business data stays on ARMRA's infrastructure. No PII traverses third-party rails without explicit governance approval. • Maintain and update the subprocessor inventory as new tools and integrations come online. • Partner with Legal and Compliance on AI-specific governance: customer disclosure requirements, model training prohibitions, vendor data protection standards, and PII handling protocols. • Own the technical side of data retention enforcement, deletion workflows, and audit trails across integrated systems. • Build and evolve the AI governance framework in partnership with Compliance, including approved tool lists, subprocessor documentation, and model training restrictions. • Cross-Functional Technical Leadership • Serve as the primary technical consultant for department heads and executive leadership on AI architecture, investment trade-offs, and long-term capability planning. • Partner with leaders across all departments — Operations, Marketing, Finance, Retail, and Customer Experience — to identify high-impact automation opportunities and translate business needs into technical requirements. • Collaborate closely with the Director of IT to ensure AI infrastructure decisions are aligned with the broader technology ecosystem and organizational standards. • Run discovery sessions with stakeholders to map current workflows, quantify manual effort, and prioritize builds based on ROI and feasibility. • Build and maintain dashboards and reporting infrastructure that give leadership visibility into AI performance, automation coverage, and operational efficiency gains across the business. • Stay current on emerging AI tools, APIs, and integration patterns. Bring recommendations with a plan, not just awareness. If something can make us faster, flag it with a build timeline.