AI & Data Architect

🔥 8 hours ago

🦌 Connecticut, Florida, +4 more states – Remote

🦌 Connecticut – Remote 🐊 Florida – Remote 🌲 North Carolina – Remote 🏈 Ohio – Remote 🔔 Pennsylvania – Remote ⚔️ Virginia – Remote

⏰ Full Time

🟠 Senior

🔴 Lead

🚰 Data Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Pitney Bowes

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1920

📦 Logistics

💼 Consulting

📣 Marketing

Logistics • Consulting • Marketing

Pitney Bowes is a technology-driven company that provides SaaS shipping solutions, mailing innovation, and financial services to clients worldwide, including more than 90 percent of the Fortune 500. It caters to a range of clients from small businesses to large enterprises and government entities, helping them reduce the complexity of sending mail and parcels. Pitney Bowes combines cutting-edge technical solutions with client services, engineering, finance, and warehouse operations to offer comprehensive support and innovation in digital commerce.

📋 Description

• 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 • Advise the CIO and business leadership on AI strategy • Design and implement modern enterprise data architecture using lakehouse, mesh, or hybrid models • Define enterprise-wide data models, canonical schemas, metadata, lineage, data catalog, integration, and interoperability strategies • Lead development of a centralized, scalable data platform • Establish enterprise AI/ML platform capabilities, including MLOps and LLMOps • Enable model lifecycle management from data ingestion through training, deployment, and monitoring • Standardize tooling, frameworks, and infrastructure for AI delivery • Drive adoption of production-grade AI patterns • Define and enforce data governance, ownership, stewardship, quality, master data, and lifecycle standards • Resolve data fragmentation and enable a single trusted data foundation • Embed responsible AI practices, including transparency, fairness, and explainability • Partner with security and risk leaders to mitigate AI risks, protect sensitive data and models, establish security standards, and implement auditability and controls • Serve as enterprise authority for AI and data architecture decisions • Define reference architectures, patterns, and reusable components • Lead architecture reviews for major data platforms and AI-enabled applications • Ensure consistency across business units and technology teams • Partner with Engineering, Product, Security, and Operations teams • Enable a federated adoption model with central platforms and distributed execution • Build and mentor a high-performing team of architects and engineers • Drive collaboration through AI councils, governance forums, and working groups • Establish and adopt an enterprise AI and data platform across business units • Reduce data fragmentation and implement clear ownership and governance • Standardize the AI delivery lifecycle with measurable improvements in speed and quality • Increase business impact from AI through revenue, cost efficiency, and decision quality • Drive consistency and reuse through architecture governance

🎯 Requirements

• 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 in data architecture: lakehouse, data mesh, ETL/ELT, streaming pipelines • Technical expertise in AI/ML: model lifecycle, MLOps, generative AI, LLM integration • Technical expertise in data governance: metadata, lineage, quality frameworks • Technical expertise in platform engineering: APIs, microservices, cloud-native architectures • Security and compliance principles for data and AI systems • 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 • Must be legally authorized to work in the US • Employer will not sponsor position for employment visa status now or in the future (e.g., H-1B)

🏖️ Benefits

• Opportunity to grow and develop your career • Inclusive environment that encourages diverse perspectives and ideas • Challenging and unique opportunities to contribute to the success of a transforming organization • Comprehensive benefits globally (PB Benefits and Wellbeing Programs)