Senior Director, Enterprise AI & Architecture

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. This is a high-visibility role at the intersection of strategy technology and compliance in the highly regulated sectors.

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.
• Partnering to define  standards for  AI-assisted software engineering practices across the SDLC including coding testing documentation requirements analysis code review and engineering workflow automation.
• 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.  Driving  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 OKRs.

Business Capability Enablement & Adoption

• Partner with engineering operations finance customer service and other business functions to identify and deliver high-value AI-enabled process improvements.
• Lead the development of AI capabilities such as decision support workflow automation document intelligence knowledge assistance summarization triage productivity tools and service quality improvements.
• Help business teams move from AI ideas to practical use cases with clear outcomes adoption plans controls and value measures.
• Lead enterprise enablement of AI productivity tools such as Gemini ChatGPT Claude and related assistants including standards training adoption practices and usage guardrails.
• Build reusable playbooks enablement models and communities of practice that raise AI fluency across IT and the broader organization.

Responsible AI Governance & Risk Partnership

• Embed security privacy responsible AI sensitive data handling human oversight vendor risk and production readiness into AI platforms business use cases engineering practices operations and employee tools.
• Partner with Security Legal Risk Compliance Data Architecture and business teams to define and operationalize enterprise AI governance. 
• Create governance models that support responsible experimentation while protecting customers employees business partners and enterprise data.
• Partner with Finance to implement FinOps guardrails cost allocation models and real-time AI spend dashboards.
• Embed responsible AI principles PCI-DSS SOX compliance ethics and explainability into every initiative.

Team Leadership Delivery & Enterprise Collaboration

• Build and lead a small high-performing AI-First organization with strong architecture engineering automation platform and delivery capabilities.
• Lead from the front with a hands-on roll-up-the-sleeves leadership style and strong ownership of outcomes. Owning delivery across scope schedule budget quality risk dependencies adoption and business value.
• Develop talent and create a culture of curiosity accountability disciplined experimentation continuous learning and measurable outcomes.
   

Qualifications :

Heres What Were Looking For

• 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.
• Bachelors 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).
• Demonstrated success building or leading an enterprise AI platform engineering or architecture function at scale.
• Proven ability to lead internal teams contractors vendors and system integration partners in a fast-paced high-accountability environment.
• Strong command of compliance requirements relevant to payments (PCI-DSS SOX)..
• Experience with FinOps practices and cloud cost governance for AI/ML workloads.

Preferred Qualifications

• Experience at a global payments fintech or healthcare technology company.
• Familiarity with federated delivery models and domain-led architecture teams.
• Background in responsible AI AI ethics frameworks or model explainability.
• MBA or advanced degree in Computer Science Engineering or related field.
   

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 $200000 - $250000 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. 

#LI-Hybrid

Remote Work :

No

Employment Type :

Full-time