Six Figure Work

Senior Director, Enterprise AI & Architecture

Flywire

Company websiteflywire.com (Flywire, opens in new tab)

Base salary $200K  to $250K

Employer-published annual base salary, USD. Advertised base range in Boston, MA

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  • LocationBoston, MA
  • WorkplaceHybrid
  • Status at last checkSource accepting applications when checked
  • Last checked (17 min ago) · observed since

About this job

Company Description

Are you ready to trade your job for a journey? Become a FlyMate!

Passion, excitement & global collaboration are all core to what it means to be a FlyMate. At Flywire, we’re on a mission to deliver the world’s most important and complex payments. We use our Flywire Advantage - the combination of our next-gen payments platform, proprietary payment network and vertical specific software, to help our clients get paid, and help their customers pay with ease - no matter where they are in the world.

What more do we need to truly be unstoppable? Perhaps, that is you! 

Who we are: 
Flywire is a global payments enablement and software company, founded more than a decade ago to solve high-stakes, high-value payments in higher education. We’ve since scaled into new regions and industry verticals and expanded our product offerings to deliver meaningful value to our clients around the world. 

Today we support more than 5,100 clients across the global education, healthcare, travel & B2B industries, with diverse payment methods across 240 countries & territories and more than 140 currencies.

With over 1,200 global FlyMates, representing more than 40 nationalities, and in 12 offices world-wide, we’re looking for FlyMates to join the next stage of our journey as we continue to grow.
 

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. 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 easy.company 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

Here's What We're 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.
  • 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).
  • 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 $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. 

#LI-Hybrid

Source: Flywire on SmartRecruiters · View original posting (opens in new tab)

Pay in context

This role's base floor ($200,000) is above 91% of the 526 Software Engineering roles in Massachusetts listed on this site; 14 others list the same floor. Their median floor is $149,000; the middle half runs from $130,000 to $172,000.

Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 8, 2026.

This range next to 4 other live Flywire roles with the nearest advertised base floor
Chart as a table
This range next to 4 other live Flywire roles with the nearest advertised base floor
RolePublished base
Senior Director, Enterprise AI & Architecture (this listing)$200K - $250K
Senior Director, Pricing and Commercial$198K - $225K
Senior Director, Head of Enterprise Architecture$245K - $295K
VP, Product Payments Experience & Customer Loyalty$250K - $300K
Manager, Talent Acquisition, AMER$117K - $146K

Same $100K to $400K scale as every card. All Flywire roles · How to read the bar

Observed changes

  1. First observed on the employer's board
  2. Began meeting the published-salary criteria
Observed since
Employer-stated posting date
2026-07-08
Where this pay comes from

Location as the employer wrote it: Boston, MA, United States

The US base salary range for this full-time position is $200,000 - $250,000 and benefits. Our salary ranges are determined by role, pos

Method
Employer text, read with fixed rules and re-verified
Checked
Rule set
us-base-v2

The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.

What we verified

  • The pay figures come from the employer's own listing, quoted exactly above.
  • The pay is an annual base salary in US dollars with a minimum of at least $100,000.
  • The role was publicly listed on the employer's job board when last checked.

We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.

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