About this opportunity
Pitney Bowes lists this AI & Data Architect opportunity in virginia, Minnesota. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Define enterprise-wide:
Data quality
Major data platforms
We’re hiring at Pitney Bowes, where top talent builds meaningful careers and lasting impact. We Move fast, Deliver excellence, and Win together…that’s The Pitney Bowes way. Here, how we work matters just as much as what we achieve.
We’re Looking For People Who
Act with urgency, accountability, and purpose
Deliver high quality work with consistency and pride
Collaborate effectively and elevate those around them
Focus on outcomes that drive impact and growth
Job Description
The AI & Data Architect is the senior technical leader responsible for defining and executing the enterprise AI and data architecture strategy . This role establishes a scalable, secure, and governed foundation for data and AI, enabling the organization to deliver measurable business outcomes through advanced analytics, machine learning, and generative AI.
The role acts as the design authority for AI and data platforms—ensuring alignment across business priorities, technology architecture, data governance, and AI capabilities—while driving consistency, reuse, and speed of delivery across the enterprise.
You Will
Enterprise AI & Data Strategy
Define and own the enterprise AI and data architecture roadmap
Align AI and data initiatives with business strategy and value realization
Establish standards for scalable, reusable AI and data capabilities
Serve as a trusted advisor to CIO and business leadership on AI strategy
Data Architecture & Platform Leadership
Design and implement a modern enterprise data architecture (lakehouse / mesh / hybrid models)
Define enterprise-wide:Data models and canonical schemas
Metadata, lineage, and data catalog strategy
Data integration and interoperability patterns
Lead the development of a centralized, scalable data platform
AI Platform & Engineering EnablementEstablish enterprise AI/ML platform capabilities (MLOps / LLMOps)
Enable consistent model lifecycle management:Data ingestion → model training → deployment → monitoring
Standardize tooling, frameworks, and infrastructure for AI delivery
Drive adoption of production-grade AI patterns vs. experimental silos
Data Governance, Quality & OwnershipDefine and enforce data governance framework beyond regulatory minimums
Clarify data ownership, stewardship, and accountability models
Establish enterprise standards for:Data quality
Master data management
Data lifecycle management
Resolve fragmentation and enable a single, trusted data foundation
Responsible AI & Risk ManagementEmbed responsible AI practices (transparency, fairness, explainability)
Ensure alignment with regulatory and internal policy requirements
Partner with security and risk leaders to:Mitigate AI-related risks
Protect sensitive data and models
Establish security standards for data and AI
Establish auditability and controls for AI systems
Architecture Governance & StandardsServe as the enterprise authority for AI and data architecture decisions
Define reference architectures, patterns, and reusable components
Lead architecture reviews for:Major data platforms
AI-enabled applications
Ensure consistency across business units and technology teams
Cross-Functional Leadership & InfluencePartner with Engineering, Product, Security, and Operations teams
Enable federated adoption model (central platform, distributed execution)
Build and mentor a high-performing team of architects and engineers
Drive collaboration through AI councils, governance forums, and working groups
You Bring
15+ years in enterprise architecture, data architecture, or AI/ML platforms
Proven experience building enterprise-scale data and AI platforms
Experience driving AI adoption from concept to production at scale
Strong background in cloud platforms (AWS, Azure, GCP) and distributed systems
Technical Expertise
Data architecture: lakehouse, data mesh, ETL/ELT, streaming pipelines
AI/ML: model lifecycle, MLOps, generative AI, LLM integration
Data governance: metadata, lineage, quality frameworks
Platform engineering: APIs, microservices, cloud-native architectures
Security and compliance principles for data and AI systems
Leadership & Operating Model
Ability to operate at both strategic and deep technical levels
Strong experience establishing enterprise standards and governance
Proven ability to influence executive stakeholders and cross-functional teams
Track record of building high-talent-density teams
Success Outcomes (12–24 Months)
Enterprise AI and data platform established and adopted across business units
Data fragmentation reduced; clear ownership and governance in place
AI delivery lifecycle standardized with measurable improvements in speed and quality
Increased business impact from AI (revenue, cost efficiency, decision quality)
Strong architecture governance model driving consistency and reuse
Key Performance Indicators (KPIs)
Business Impact
AI-driven revenue contribution and cost optimization
Adoption of data and AI capabilities across business units
Platform & Delivery
Time-to-deploy AI models
Platform adoption rate (% of workloads on standardized platform)
Data Quality & Governance
% of critical data assets with defined ownership
Data quality score improvements
AI Effectiveness
Model performance (accuracy, drift, business outcome metrics)
AI project ROI
Risk & Compliance
% of AI systems under governance
Reduction in data and AI-related risk incidents
Sponsorship
Must be legally authorized to work in the US. Employer will not sponsor position for employment visa status now or in the future (ex. H-1B).
We Will
Provide the opportunity to grow and develop your career
Offer an inclusive environment that encourages diverse perspectives and ideas
Deliver challenging and unique opportunities to contribute to the success of a transforming organization
Offer comprehensive benefits globally (PB Benefits and Wellbeing Programs)
Pitney Bowes is an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard for race, color, sex, religion, national origin, age, disability (mental or physical), veteran status, sexual orientation, gender identity, or any other consideration made unlawful by applicable federal, state, or local laws.
All qualified applicants, including Veterans and Individuals with Disabilities, are encouraged to apply.
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Worksite address
virginia, MN, 55792, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.