Senior Lead AI Engineer - G&A Systems

Klaviyo•Boston, MA

14h

About The Position

Klaviyo is seeking its first dedicated AI engineer within the Finance Technology (G&A FinTech) team. This foundational role will shape the architecture, standards, and long-term vision for embedding AI into Finance operations. The engineer will partner with teams across Accounting, Tax, Treasury, FP&A, Procurement, and Internal Audit, as well as Corporate IT, Data, and GTM Systems, to support a reliable, integrated, compliant finance technology stack for a public, AI-forward SaaS business. The role focuses on reimagining Finance workflows through AI, designing and building AI-powered workflows, copilots, and agents, and integrating systems across enterprise financial platforms. The engineer will help establish best practices for AI system design, orchestration, testing, security, observability, and evaluation; identify high-impact opportunities to replace manual processes; and define success metrics for efficiency and operational effectiveness. The role also includes responsible AI governance for sensitive financial data, cross-functional alignment on shared AI infrastructure and standards, and enabling Finance teams through reusable frameworks, playbooks, and training. As a technical leader, this person will help set direction for scalable, well-governed AI systems and influence how Klaviyo becomes AI-first internally, beginning with Finance systems.

Requirements

At least 5 years of engineering or data engineering experience.
At least 2 years building AI/ML or LLM-powered solutions that deliver tangible business outcomes.
Proven ability to set technical direction and build 0-to-1 systems with meaningful organizational impact.
Strong experience with technologies such as React, JSON, Python, SQL, and modern APIs.
Experience with LLM platforms such as OpenAI, Claude, or Gemini.
Experience designing AI-powered workflows, agents, or copilots.
Experience integrating with Finance systems through Runlayer and MCPs.
Experience integrating enterprise financial SaaS systems.
Experience designing scalable and secure systems, automation frameworks, and internal tools.
Experience working with sensitive data and implementing responsible AI practices.
Ability to translate ambiguous business problems into scalable technical solutions.
Passion and curiosity for experimenting with and reimagining Finance workflows.

Nice To Haves

Experience with financial systems such as NetSuite, Zip, Avalara/Vertex, Zone Advanced Billing, or equivalent systems.
Familiarity with SOX and ITGCs.
Familiarity with middleware automation platforms such as n8n, Workato, or Zapier.
Experience in high-growth SaaS environments.
Contributions to AI governance, internal AI platforms, or experimentation frameworks.

Responsibilities

Reimagine core Finance workflows, including accounting, procurement, deal desk approvals, revenue, and month-end/quarter-end close, through an AI-first lens.
Design and build AI-powered workflows, copilots, and agents to automate and augment Finance processes.
Architect and implement integrations across SaaS platforms such as NetSuite, Zip, Zone Advanced Billing, and Avalara/Vertex.
Partner with the internal IT AI team to establish best practices for prompt engineering and evaluation, LLM system design and orchestration, and AI system versioning, testing, security, and observability.
Enable AI use cases that improve Finance teams’ execution and decision-making.
Collaborate with stakeholders to translate business problems into scalable AI solutions.
Identify high-leverage opportunities to replace manual workflows with AI-native solutions.
Define and track success metrics for efficiency gains, time savings, and operational effectiveness.
Advise Finance leadership on AI opportunities and possibilities.
Design systems that protect sensitive financial data and support security, privacy, and trust.
Partner with Internal Audit, Security, Legal, and Global IT to ensure compliant and ethical AI deployment.
Align with Security, Global IT, and GTM Systems on shared AI infrastructure and standards.
Contribute to and adopt company-wide AI patterns, tooling, and best practices.
Build reusable frameworks, workflows, playbooks, and training materials to enable Finance teams to use AI-powered tools.
Help non-technical stakeholders confidently use and iterate on AI-powered tools.
Advocate for scalable, well-governed AI systems that integrate cleanly into Klaviyo’s broader technology ecosystem.
Help shape how Klaviyo becomes AI-first internally, starting with Finance systems.