Ai Risk Jobs in Spring, TX (NOW HIRING)

Job Description: Description Alvarez & Marsal (A&M) is a global consulting firm with over 10,000 entrepreneurial, action and results-oriented professionals in over 40 countries. We take a hands-on approach to solving our clients' problems and assisting them in reaching their potential. Our culture celebrates independent thinkers and doers who positively impact our clients and shape our industry. The collaborative environment and engaging work—guided by A&M's core values of Integrity, Quality, Objectivity, Fun, Personal Reward, and Inclusive Diversity—are why our people love working at A&M. A&M's Private Equity Performance Improvement Services (PEPI) practice focuses on serving upper middle market and large cap private equity firms who have engaged A&M to help improve operating results at their portfolio companies ($50M–$1B+ revenue range). Our PEPI services include: IT / Product / Engineering [Technology Services] CDD/Strategy Interim Management Merger Integration & Carve-outs Rapid Results Supply Chain CFO Services Technology Services – CIO Domain The Technology Services team works directly with private equity firms and their portfolio companies to drive measurable value through applied AI. Within the CIO Domain, our engagements target the enterprise IT organization—infrastructure, systems of record, cybersecurity, and IT operations—helping portfolio companies embed AI to reduce cost, strengthen resilience, and accelerate IT-enabled business outcomes. Specific focus areas include: AI-enabled IT operating model design and enterprise architecture modernization AIOps and intelligent IT operations: predictive incident management, automated remediation, and self-healing infrastructure AI governance frameworks: AI-powered capabilities, model standards and lifecycle oversight, and AI capabilities risk management Data governance: metadata and data classification, lineage and quality standards, access controls, retention and regulatory compliance oversight Cloud infrastructure readiness for AI workload deployment (Azure, AWS, GCP) Cybersecurity and AI risk: embedding AI-era controls across identity, access management, threat detection, and security operations AI-embedded enterprise systems: Experience leveraging AI-native capabilities within core systems of record (SAP, Oracle, Workday, ServiceNow), including embedded copilots, intelligent automation, predictive workflows, and vendor AI roadmap evaluation Data platform & BI transformation: Track record leading large-scale data platform modernization — including cloud and modern data platform architecture spanning hyperscalers and data-lake environments, enterprise data governance, and business intelligence enablement — to support AI-ready, insight-driven decision-making at scale Establishment of FinOps for cloud and AI/ML operation capabilities and processes. IT cost optimization through intelligent automation of service desk, IT operations, and infrastructure management End-to-end transformation execution, governance, and value tracking tied to IT financial targets We align AI initiatives with investment theses, financial targets, and operational realities to ensure durable impact. Role Overview As a Director in the PEPI Technology Services AI team [CIO Domain], you will independently lead AI-driven value creation engagements across the private equity lifecycle, with a specific focus on the CIO organization of PE-backed portfolio companies. You own scope, workplan, client relationships, and financial outcomes end-to-end. You are the senior accountable leader on the engagement. This role requires a practitioner who has operated inside or directly alongside CIO organizations—someone who has personally led IT transformations, managed vendors, governed AI deployments, or run enterprise technology programs—and who can translate that hands-on operating experience into rapid, credible impact within the compressed timelines of a PE holding period. How You Will Contribute Engagement Leadership & Client Ownership Establish and champion the full engagement lifecycle: develop and roll-out playbooks for scoping, workplanning, team management, executive communications, and financial delivery against defined and productized AI targets Serve as primary point of contact for portfolio company CIOs, IT leadership teams, and PE deal partners—building trusted advisor relationships that extend across the holding period Lead cross-functional engagement teams spanning enterprise architecture, infrastructure, security, data, and IT operations Drive executive-level workshops and steering committee presentations; translate complex IT findings into clear financial and operational narratives for PE audiences AI Strategy, Diligence & Value Creation Identify and prioritize AI use cases within the CIO domain mapped directly to EBITDA improvement, IT cost reduction, and risk mitigation Lead AI-focused diligence workstreams: assess IT infrastructure maturity, data estate readiness, AI governance capabilities, cybersecurity posture, and ERP landscape to size value potential Develop AI-enabled IT operating models and transformation roadmaps with specific financial targets, milestones, and accountability structures Assess platform-native AI capabilities within ERP and ITSM systems and design adoption roadmaps within PE holding period constraints Transformation Execution & Governance Establish program governance, KPI frameworks, and value tracking tied to IT metrics: MTTR, SLA compliance, automation rate, incident deflection rate, and IT cost per user Manage vendor relationships, managed service providers, and implementation partners across timelines, budgets, and execution risks Redesign core IT processes to embed AI into operations: AIOps-driven incident triage, AI-assisted change management, automated compliance monitoring, and self-service IT portals Align IT organizational structures and talent models to support AI-augmented operations Practice Contribution Support business development: contribute to proposals, respond to PE firm RFPs, and participate in client pitches Mentor Senior Associates and Analysts; contribute to A&M's Technology Services methodology, tools, and accelerators for CIO domain engagements Required Skills & Technology Fluency Directors are expected to have demonstrated experience of successfully navigating, rolling out and governing implementations using the technologies below, not merely advised on them. Candidates should be able to speak to specific programs they have run, financial outcomes they delivered, and technical decisions they owned. Enterprise-wide and Organizational IT AI Strategy & Governance Design and operationalize enterprise Data and AI governance frameworks: AI powered capabilities and model risk policies, AI acceptable use standards, data lineage and usage controls, and model lifecycle management from deployment through decommission Define and implement AI Center of Excellence (CoE) structures within IT organizations: staffing models, operating procedures, intake processes, and build-vs-buy evaluation frameworks Conduct AI readiness assessments across IT domains—data quality, infrastructure elasticity, security posture, and organizational change capacity—and translate findings into investment-grade business cases Establish KPIs and value tracking mechanisms for AI initiatives tied directly to EBITDA levers: IT cost per user, automation rate, mean time to resolve (MTTR), incident deflection rate, and SLA compliance Navigate AI regulatory and compliance risk in enterprise IT contexts: GDPR/CCPA implications for AI data use, SOC 2 audit requirements for AI systems, and NIST AI RMF alignment AIOps & Intelligent IT Operations Deploy and tune AIOps platforms—Dynatrace, Datadog, Splunk ITSI, New Relic, IBM AIOps Insights, LogicMonitor—including alert correlation rules, anomaly detection thresholds, and automated remediation playbooks Architect self-healing infrastructure pipelines: event-driven orchestration using ServiceNow ITOM, PagerDuty, xMatters, or equivalent—from anomaly detection through root cause analysis to auto-remediation Configure and govern CMDB in ServiceNow or BMC Helix: CI relationships, dependency mapping, and service maps that underpin AIOps accuracy Implement AI-enhanced service desk capabilities: conversational AI agents (ServiceNow Now Assist, Microsoft Copilot Studio), intelligent ticket classification and routing, and self-service deflection measurement Deploy log intelligence and observability stacks: Splunk SPL for ML-based alerting, Elastic/ELK with anomaly detection, OpenTelemetry instrumentation standards, and distributed tracing across hybrid environments Define and track IT operations metrics: MTTR, MTTD, change success rate, incident volume trends, and cost per ticket—with AI uplift quantified against baseline Cloud Infrastructure & AI Workload Readiness Architect cloud environments for AI workload deployment: GPU/TPU compute provisioning on Azure (ND-series, NC-series), AWS (P-series, Inf), and GCP (A100/H100 instances); cost governance for AI compute spend Design and govern cloud landing zones and AI-ready infrastructure patterns: Azure AI Foundry, AWS SageMaker, Google Vertex AI—including network segmentation, private endpoints, and data residency controls Implement and govern Infrastructure as Code at scale: Terraform modules, Ansible playbooks, Azure Bicep templates—with AI-assisted IaC generation and validation pipelines Lead hybrid and multi-cloud architecture decisions: workload placement strategy, cloud cost optimization (FinOps), and AI platform consolidation within PE holding period capital constraints Govern identity and access for AI systems: Microsoft Entra ID (Azure AD) conditional access policies, Okta workforce identity, CyberArk PAM for service account management, and zero-trust architecture for AI workloads ERP & Systems of Record Transformation Lead AI-augmentation programs on major ERP platforms: SAP S/4HANA with SAP Joule (AI copilot for finance, procurement, supply chain), Oracle Cloud ERP/HCM with Oracle Fusion AI, Workday Finance and HCM with Workday AI, Microsoft Dynamics 365 Copilot Scope and govern ERP AI use cases within PE holding period constraints: automated journal entry creation, AI-assisted reconciliation, intelligent vendor invoice processing, predictive demand planning, and Copilot-driven financial close acceleration Design and oversee data integration architectures connecting ERP systems to AI platforms: MuleSoft Anypoint, Azure Data Factory, Boomi, or equivalent—including data quality frameworks that gate AI model reliability Assess and manage technical debt within ERP landscapes: identify customizations that block AI-native feature adoption and build remediation roadmaps tied to EBITDA targets Lead master data governance initiatives required for AI accuracy: MDM platform selection (Informatica, Stibo, SAP MDG), data stewardship models, and golden record management Cybersecurity & AI Risk Management Design AI-era security architectures: zero-trust network access (ZTNA), microsegmentation, AI-augmented SIEM/SOAR platforms (Microsoft Sentinel, Splunk SOAR, Palo Alto XSIAM), and extended detection and response (XDR) Govern AI-specific security risks: prompt injection controls, model access governance, training data poisoning prevention, and AI output monitoring for data exfiltration Implement and assess against security frameworks: NIST CSF 2.0, CIS Controls v8, ISO 27001, SOC 2 Type II—with explicit mapping to AI system requirements Lead identity security programs: privileged access management (CyberArk, BeyondTrust), identity governance and administration (SailPoint, Saviynt), and AI-assisted access certification Oversee third-party and supply chain AI risk: vendor AI security assessments, AI model provenance, and contractual AI data usage controls AI & Automation Platform Development Architect and govern enterprise LLM deployments: Azure OpenAI Service, AWS Bedrock, Google Vertex AI—including prompt governance, retrieval-augmented generation (RAG) pipelines, model versioning, and cost controls Design agentic AI workflows for IT automation: multi-agent orchestration (AutoGen, LangGraph, CrewAI) applied to ITSM, infrastructure management, and security operations use cases Implement and govern low-code/no-code AI automation platforms: Microsoft Power Platform (Power Automate, Copilot Studio), ServiceNow Agentic AI, UiPath Autopilot, or equivalent—including governance guardrails, approval workflows, and audit trails Evaluate and select AI data platforms: Snowflake Cortex AI, Databricks Mosaic AI, Microsoft Fabric—and architect data pipelines that feed AI models with governed, high-quality enterprise data Build and govern LLM application frameworks for CIO domain use cases: LangChain, LlamaIndex—applied to knowledge management, IT runbook automation, and enterprise Q&A systems Qualifications 8–12+ years in IT strategy, enterprise architecture, IT operations, or technology transformation—with a meaningful portion in hands-on operator or senior practitioner roles, not exclusively advisory Demonstrated track record of leading complex, multi-workstream IT transformation programs with measurable financial outcomes—cost reductions, EBITDA improvements, or working capital savings delivered and realized Tangible operating experience within or directly alongside CIO organizations: has personally managed IT programs, governed enterprise technology platforms, led vendor relationships, or run IT operations at a company—not just advised on them Experience working with private equity firms or PE-backed portfolio companies, with understanding of deal timelines, value creation plans, and exit preparation Proven ability to manage senior client relationships at the CIO, CFO, or CEO level and translate IT complexity into financial impact narratives Education Undergraduate degree in computer science, information systems, engineering, or a related technical field strongly preferred; MBA or advanced degree preferred Relevant certifications valued: Azure Solutions Architect Expert, AWS Solutions Architect Professional, Google Professional Cloud Architect, CISSP, CISM, ITIL 4 Managing Professional, ServiceNow Certified Implementation Specialist, SAP Certified Associate Preferred Background Experience at a top-tier consulting firm, systems integrator, or managed service provider with a CIO/IT transformation focus Operator experience: prior role as VP of IT, Director of IT, IT Program Director, or equivalent inside a PE-backed or mid-market company Track record of AIOps deployments, ERP modernizations, IT cost takeout programs, or cybersecurity transformation with quantified PE-relevant outcomes Compensation: $150,000 – $225,000 base salary annually, dependent on education, experience, skills, and geography, plus a dis