Manager, Software Engineering - AI and Data Platform

Blackbaud is a company focused on powering social impact through purpose-driven technology and responsible AI. The Engineering Manager for the Data & AI Platform will lead teams in building and evolving the enterprise Data & AI platform, ensuring it is scalable, secure, and aligned with business outcomes for the nonprofit sector.

Responsibilities:

• Own and evolve core Data & AI platform capabilities, including ingestion, transformation, lakehouse architecture, feature services, and AI/ML enablement layers
• Drive platform decisions aligned with Blackbaud’s Unified Data & AI Platform Strategy (modularity, interoperability, AI‑first design)
• Partner with Architecture, Governance, and Security to ensure the platform meets trust, compliance, and Responsible AI standards
• Balance build vs. buy decisions, prioritizing core competencies while reducing operational complexity
• Lead teams to deliver high‑impact platform initiatives aligned to AOP priorities (legacy modernization, cloud migration, cost optimization, agent enablement)
• Ensure platform reliability through operational excellence, including monitoring, incident management, and performance optimization
• Establish clear roadmaps, milestones, and success metrics for platform initiatives
• Hire, mentor, and grow high‑performing platform engineers across geographies
• Provide regular feedback, coaching, and career development aligned with Blackbaud’s people strategy
• Ensure every team member has clear goals, an active IDP, and opportunities to grow in modern Data & AI skills
• Collaborate closely with Product, Data Science, Analytics, and Product Engineering teams to ensure the platform accelerates—not blocks—delivery
• Influence standards and best practices across the Data Intelligence COE

Requirements:

• 8+ years of experience in software, data, or platform engineering (.NET, Azure, Databricks, ADO preferred)
• 3+ years of experience managing and developing data engineering teams
• Hands‑on experience with modern data platforms, cloud data lakes/lakehouses, distributed processing, streaming, APIs
• Strong understanding of platform engineering principles and operating production systems at scale
• Proven ability to lead through ambiguity and influence without authority