Senior Director, Enterprise AI & Architecture

Job Description

The Opportunity
Flywire is building a centralized Enterprise AI organization to govern, scale, and accelerate AI adoption across the business. The Sr. Director, Enterprise AI & Architecture will found and lead this function, establishing the enterprise-wide standards, governance model, shared platform strategy, and talent infrastructure needed to deliver measurable business value.

Key Responsibilities
AI Platforms, Architecture & Engineering Enablement
- Define and own the Enterprise AI strategy, roadmap, and operating model in alignment with
- Build and lead team spanning architecture, AI engineering, platform, governance, and security.
- Leading the strategy and delivery of foundational AI platform capabilities that support secure, scalable, and reusable AI-enabled applications.
- Serve as strategic leader for the AI Center of Excellence; represent the Enterprise AI org to the Executive team reporting on milestones, ROI, and risk posture.
- Define architecture patterns for AI-First applications, copilots, intelligent workflows, automation agents, enterprise knowledge solutions, and reusable AI components.
- Oversee a risk-tiered governance and architecture review process; own the technology exception process.
- Guide platform capabilities such as model access, retrieval frameworks, vector databases, enterprise knowledge integration, prompt and response controls, observability, and governance guardrails.
- Partner with Applications, Engineering, Infrastructure, Operations, Architecture, Security, and Data teams to pilot, refine, and scale AI-enabled practices over time.
- Establish and maintain enterprise AI/ML standards, frameworks, playbooks, and reference architectures.
- Drive adoption of a centralized AI platform including LLM gateway, model registry, agent frameworks, and shared APIs.
- Evaluate emerging AI vendors and technologies; run pilot programs and proofs-of-concept.
- Prevent shadow AI proliferation by providing self-service resources and pre-approved patterns that make governance easy.

Qualifications

• 15+ years of progressive technology leadership experience, including senior responsibility for engineering, architecture, platforms, data, infrastructure, automation, AI, digital transformation, or enterprise technology delivery, including 5+ years managing multi-disciplinary engineering or architecture teams.
• Experience at large Enterprise, enabling enterprise adoption of AI productivity tools such as Gemini, ChatGPT, Claude, or similar platforms.
• Significant hands-on leadership experience with AI, machine learning, Generative AI, automation, advanced analytics, intelligent platforms, developer productivity tools, or emerging technology capabilities, at a large Enterprise Organization.
• Strong understanding of Generative AI concepts and implementation patterns, including LLMs, RAG pipelines, agentic AI frameworks, enterprise ML deployment patterns, SLMs, embeddings, prompt engineering, retrieval-augmented generation, vector databases, semantic search, evaluation frameworks, and enterprise knowledge integration.
• Experience with Agentic AI patterns, including autonomous or semi-autonomous agents, tool/function calling, workflow orchestration, human-in-the-loop controls, guardrails, monitoring, and safe deployment practices.
• Familiarity with Model Context Protocol (MCP) or similar approaches for connecting AI systems to enterprise tools, data sources, APIs, and workflow actions in a secure and governed manner.
• Understanding of AI/ML model lifecycle practices, including model selection, experimentation, validation controls, performance monitoring, drift detection, feedback loops, auditability, and responsible production deployment.
• Familiarity with enterprise AI platform capabilities such as model access gateways, model catalogs, AI orchestration layers, policy enforcement, prompt and response controls, observability, cost monitoring, and usage governance.
• Strong technical fluency across cloud platforms, APIs, microservices, data platforms, observability, automation, cybersecurity, identity, privacy, and modern engineering practices.
• Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or related field required.
• Leadership Attributes
  - Inspirational thought leader with passion for building and scaling AI-enabled technology and business capabilities.
  - Pragmatic, hands-on leader with strong bias for action and measurable outcomes.
  - Strategic yet technical, with ability to dive deep into architecture, engineering, security, data, operations, and business process details.
  - Proven experience leading Enterprise-scale technology transformation; preferably in a regulated environment, such as financial services, or another highly governed industry.
  - Track record of partnering with executive stakeholders and translating technology strategy into business outcomes.
  - Experienced at defining and influencing organizational strategy, inclusive of board and executive level communications(written and verbal).
• Experience with FinOps practices and cloud cost governance for AI/ML workloads.

Additional Information

Submit today and get started! We are excited to get to know you! Throughout our process you can expect to meet different FlyMates including the Hiring Manager and other Flymates. Your Talent Acquisition Partner will walk you through the steps and be your “go-to” person for questions.

Flywire is an equal opportunity employer and follows a policy of administering all employment decisions and personnel actions without regard to race, color, religion, sex, pregnancy, gender identity, national origin, age, ancestry, physical or mental disability, sexual orientation, genetic disposition or carrier status, veteran status, or any other category protected under applicable national, federal, state or local law. The US base salary range for this full-time position is $200,000 - $250,000 and benefits. Our salary ranges are determined by role, position level, and location. The range displayed on this job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and several other factors, including job-related skills, experience, relevant education and training.