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Head of Artificial Intelligence Orchestration

Job in Oaks, Montgomery County, Pennsylvania, 19456, USA
Listing for: SEI
Full Time position
Listed on 2026-03-01
Job specializations:
  • IT/Tech
    AI Engineer
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below
Location: Oaks

SEI is hiring a Head of AI Orchestration, responsible for orchestrating how artificial intelligence reshapes SEI's business, operating and talent models. This role focuses on moving AI from experimentation to scaled, ethical, and measurable enterprise impact by driving enterprise learning, adoption, workflow reinvention, governancebydesign, and value realization across all business units.

Operating horizontally across the firm, this leader ensures AI becomes a durable source of competitive advantage by embedding it into how SEI learns, works, decides, and grows - not just how technology is built.

This role reports into the Chief Operating Officer, with a dotted line into the Head of SEI Next. The role operates as a peer to the Chief Technology Officer (CTO) and works horizontally across Product, Technology, Operations, Risk, Compliance, all Business Units and SEI Next. This role is not embedded within a specific function because of the broad and transformative nature of the work.

The role requires highly collaborative and strategic leadership, and will foster deep curiosity, challenge existing ways of operating, establish new standards, and ensure the approach to AI at SEI moves from experimentation to measurable business impact. Success will be measured using outcome-based metrics aligned with leading industry practice, including:

  • Revenue per employee and productivity per role
  • Active usage of AI by employees in core workflows
  • AI Champion program participation, training completion, and peer-led impact
  • Number of end-to-end processes reimagined or eliminated
  • Cycle time reduction from idea production scale
  • Governance coverage, audit readiness, and AI related incident rates
1. Enterprise AI Strategy & Direction
  • Orchestrate the creation and maintenance of SEI's enterprise AI vision, strategy, and multiyear roadmap.
  • Determine where AI should be applied across products, operations, and internal workflows.
  • Establish priorities and sequencing across build, buy, partner, and whitelabel AI approaches. Facilitate the build, buy, partner decision-making forum for SEI.
  • Continuously assess SEI's competitive AI posture relative to peers and emerging market leaders.
2. AI-Enabled Products & Business Value
  • Partner with the Chief Technology Officer and Chief Product Officer to embed AI into client facing products where it drives differentiation, revenue, or retention.
  • Serve as the enterprise orchestrator of how AI is designed, sourced, and deployed within products.
  • Ensure AI initiatives progress from pilot to production with clear ownership, timelines, and outcomes.
  • Hold accountability for measurable business impact (e.g., revenue growth, cost reduction, productivity gains). Establish and maintain enterprise-level measurement frameworks for AI impact, and partner with business and functional leaders to ensure shared accountability for outcomes such as productivity, growth, learning velocity, and trust.
3. Partnership & Ecosystem Leadership
  • Partner closely with SEI Next and Corporate Development teams to shape and execute the firm's AI partnership and investment strategy.
  • Orchestrate SEI's AI ecosystem, including strategic partners (e.g., Microsoft, IBM), startup portfolio companies, and emerging AI platforms.
  • Translate partner capabilities into practical enterprise adoption and learning, avoiding isolated pilots and ensuring reuse, scale, and measurable impact.
4. AI Governance, Risk & Compliance Enablement
  • Lead SEI's AI governance model, ensuring responsible, secure, and compliant use of AI.
  • Partner with Legal, Risk, Compliance, Vendor Management and Security to modernize data, AI, and intellectual property clauses in vendor and client agreements.
  • Ensure AI governance enables innovation at scale while maintaining trust, transparency, audit readiness, and regulatory compliance.
  • Establish controlled environments (pilots, sandboxes, phased releases) to test and deploy AI safely.
5. Operating Model & Enterprise Enablement
  • Cocreate, evolve, and steward SEI's AI operating model in partnership with business units and functions, ensuring it is practical, adopted, and continuously improved.
  • Set enterprise standards framework for AI tooling, models, agents, and reuse across teams.
  • Align enterprise AI priorities, sequencing, and roadmaps in partnership with business units and functional leaders, ensuring focus, reuse, and scalable impact without constraining local innovation.
6. Talent, Culture & AI Fluency
  • Drive a firmwide learning mindset where AI is treated as a teammate and accelerator, not merely a tool.
  • Champion AI literacy and adoption across SEI. Scale and evolve SEI's AI Champion program as the primary engine for peerled learning, experimentation, and enterprise adoption.
  • Partner with People & Culture to upskill leaders and teams on applied AI use cases, and embed AI into leadership development, role-based capability building, and evolving performance expectations. Build and retain high impact AI, product, and applied analytics talent.
  • Foster a culture of…
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