AI & Data Architect

Posted 2 Months Ago
Hiring Remotely in Shelton, CT, USA
In-Office or Remote
Expert/Leader
Information Technology • Logistics • Financial Services
The Role
Senior technical leader responsible for enterprise AI and data architecture. Own the AI/data strategy and architecture roadmap, build scalable cloud-native data and AI platforms (lakehouse, data mesh), establish MLOps/LLMOps and model lifecycle practices, enforce data governance and responsible AI, partner with security and product teams, and mentor architecture and engineering teams to drive production-grade AI adoption.
Summary Generated by Built In

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

1. 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

2. 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

3. AI Platform & Engineering Enablement

  • Establish 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
4. Data Governance, Quality & Ownership
  • Define 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

5. Responsible AI & Risk Management

  • Embed 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

6. Architecture Governance & Standards

  • Serve 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

7. Cross-Functional Leadership & Influence

  • Partner 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. 

All interested individuals must apply online. Individuals with disabilities who cannot apply via our online application should refer to the alternate application options via our Individuals with Disabilities link. 

Skills Required

  • 15+ years enterprise architecture, data architecture, or AI/ML platform experience
  • Proven success building enterprise-scale data and AI platforms and driving production adoption
  • Experience driving AI adoption from concept to production at scale
  • Strong background with AWS, Azure, and GCP
  • Technical depth across lakehouse, data mesh, ETL/ELT, streaming pipelines, and cloud-native architectures
  • Experience with model lifecycle management, MLOps, LLMOps, generative AI, and LLM integration
  • Experience with metadata, lineage, canonical schemas, and MDM
  • Understanding of security and compliance requirements for data and AI systems
  • Experience establishing enterprise standards, governance, and architecture review processes
  • Proven ability to influence senior stakeholders and lead cross-functional teams
  • Track record of building and mentoring high-performing architecture and engineering teams
  • Must be legally authorized to work in the US; employer will not sponsor visas

Pitney Bowes Inc. Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Pitney Bowes Inc. and has not been reviewed or approved by Pitney Bowes Inc..

  • Healthcare Strength — Health coverage includes medical, dental, and vision options plus mental health support, FSAs/HSAs, an Employee Assistance Program, and wellness offerings. Feedback suggests these features are a notable bright spot within total rewards.
  • Retirement Support — Retirement offerings include a 401(k) with company match and a pension plan, alongside financial protections and an Employee Stock Purchase Plan. These elements pair with solid insurance to strengthen overall financial security.
  • Parental & Family Support — Family supports include paid parental leave and adoption assistance, complemented by family medical leave. These programs align with broader leave options to support caregiving needs.

Pitney Bowes Inc. Insights

Am I A Good Fit?
beta
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.

The Company
HQ: Stamford, CT
12,066 Employees
Year Founded: 1920

What We Do

Pitney Bowes (NYSE:PBI) is a global shipping and mailing company that provides technology, logistics, and financial services to more than 90 percent of the Fortune 500. Small business, retail, enterprise, and government clients around the world rely on Pitney Bowes to remove the complexity of sending mail and parcels. For additional information visit Pitney Bowes at www.pitneybowes.com.

Similar Jobs

RTX Logo RTX

Solutions Architect

Aerospace • Defense
Remote
CT, USA
185000 Employees
132K-252K Annually

RTX Logo RTX

Architect

Aerospace • Defense
Remote
CT, USA
185000 Employees
132K-252K Annually

Coretek Services Logo Coretek Services

Architect

Cloud • Information Technology • Consulting
Remote
United States
147 Employees

phData Logo phData

Architect

Information Technology
Remote
US
202 Employees

Similar Companies Hiring

Hanover Park Thumbnail
Artificial Intelligence • Fintech • Software • Financial Services
New York, New York
42 Employees
Golden Pet Brands Thumbnail
Digital Media • eCommerce • Information Technology • Marketing Tech • Pet • Retail • Social Media
El Segundo, California
178 Employees
Onshore Thumbnail
Artificial Intelligence • Fintech • Software • Financial Services
New York, New York
60 Employees

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account