Senior Director, Data & AI

Unisys

. Define the global Data & AI vision, strategy, and multi-year roadmap aligned to company growth, profitability, and client-outcome goals .

Posted 10/22/2026full-timeUnited StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive expertise in defining and executing Data & AI strategies, managing large-scale projects, and leading diverse technical teams. Proficient in data governance, cloud platforms, and responsible AI practices, with a strong focus on client engagement and financial performance.

Highest-signal resume keywords

Data GovernanceCloud Data PlatformsMachine LearningClient-Facing SkillsExecutive-Level Communication

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringAnalyticsGenerative AIAgentic AIMLOpsData PlatformsAI ServicesProject DeliveryFinancial ManagementTechnical Leadership

Soft Skills

Influencing Without AuthorityCoachingTeam BuildingClient EngagementCommunication

Tools & Technologies

AWSMicrosoft AzureGoogle CloudData Integration ToolsAnalytics Platforms

Certifications & Qualifications

Data CertificationsAI Certifications

Industry Keywords

Data & AI StrategyRegulatory ComplianceMarket TrendsInvestment PrioritiesHyperscaler Partnerships

Tech Stack

Tools & technologies

AWSAzureCloud

About the role

Key responsibilities & impact

Define the global Data & AI vision, strategy, and multi-year roadmap aligned to company growth, profitability, and client-outcome goals
Set technology direction across data platforms, engineering, integration, analytics, machine learning, generative AI, and agentic AI
Guide clients and internal teams toward modern, well-governed data estates before and alongside AI adoption
Track market trends, hyperscaler and partner roadmaps, regulation, and emerging technology and turn them into investment priorities
Sponsor pilots, proofs of concept, and accelerators and move proven ideas into production
Own delivery of Data & AI engagements from design through production
Set delivery standards for quality, security, cost, and timelines and intervene in high-risk or strategic engagements
Establish reusable methods, accelerators, reference architectures, and tooling
Build and run the production operating model, including MLOps, monitoring, support, and continuous improvement
Establish architecture principles for secure, scalable, cost-efficient data and AI platforms across cloud and hybrid environments
Establish data governance covering quality, lineage, privacy, security, and regulatory compliance
Define and apply responsible-AI policies and testing standards
Advise client executives on data and AI strategy and build relationships leading to repeat and expanded work
Support Sales and Presales on strategic pursuits, including solution shaping, orals, workshops, and delivery risk
Build strategic relationships with hyperscalers, platform vendors, and alliance partners
Contribute to pricing, estimation, and commercial models
Represent the company at industry events, with analysts, and in the market
Own revenue, margin, utilization, and budget targets and report performance to senior leadership
Plan capacity and hiring against demand
Manage delivery, financial, and security risk
Set decision rights and ways of working across business functions
Build and lead a global team of data engineers, data scientists, AI engineers, architects, and consultants
Hire, develop, and retain talent with career paths, succession plans, and continuous learning
Set skills and certification goals
Coach leaders and teams on technical excellence, client engagement, and executive communication
Align organization structure, skills, and ways of working to support innovation and growth

Requirements

What you’ll need

15+ years of experience in data, analytics, AI, or technology consulting, including 8+ years leading large, global technical teams
Deep technical knowledge across modern data platforms, data engineering, analytics, machine learning, generative AI, and agentic AI, with solutions taken from design into production
Hands-on understanding of cloud data platforms and AI services from major hyperscalers, such as AWS, Microsoft Azure, and Google Cloud
Knowledge of data governance, security, and responsible-AI practices
Track record of delivering large, complex Data & AI programs on time, on budget, and to quality standards
Experience owning financial targets such as revenue, margin, utilization, and budget
Strong client-facing skills, including advising senior executives and supporting pursuits for large enterprise or public-sector clients
Ability to work across Sales, Delivery, Engineering, Finance, Legal, and partner organizations and influence without direct authority
Executive-level communication skills, with the ability to explain complex topics simply
Bachelor's degree in computer science, data science, engineering, or a related field
Recent data or AI certifications are preferred
Applicant should be eligible for any required U.S. Government authorizations for access to export-controlled commodities and technology