Senior Lead AI Engineer - G&A Systems
Klaviyo San Francisco, CAEst. Est. USD 200,000–260,000 / yearSenior
Estimated range based on role, country and industry — not published by the company.
Key requirements
- Python
- React
- Sql
- Llm
- Oracle
- Erp
- Audit
At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements. If you’re a close but not exact match with the description, we hope you’ll still consider applying. Want to learn more about life at Klaviyo? Visit klaviyo.com/careers to see how we empower creators to own their own destiny.
Klaviyo is building an AI-first company—and that starts with how we support and scale our people.
We’re looking for a Senior Lead AI Finance Technology Engineer to be the first dedicated AI engineer within our Finance Technology (G&A FinTech) team. As an early leader in this space, you’ll reimagine how our Finance teams operate in an AI-first world by shaping our architecture, standards, and long-term vision.
You’ll partner across all Finance functions - Accounting, Tax, Treasury, FP&A, Procurement, and Internal Audit, as well as adjacent technology teams like Corporate IT, Data, and GTM Systems, to ensure our back‑office stack is reliable, well‑integrated, compliant, and ready for a public, AI‑forward SaaS business. We own the roadmap, health, and governance of platforms including our ERP and financial systems (e.g., NetSuite/Oracle), procure‑to‑pay (e.g.,Zip), revenue and billing systems, and related integrations and automation. This role is not just about applying AI it’s about defining how AI becomes embedded into the Finance at Klaviyo.
What You’ll Be Doing
AI-First Finance Systems & Architecture
Reimagine core Finance workflows (accounting, procurement, deal desk approvals, revenue, ME/QE close cycle etc., ) through an AI-first lens, not just incremental automation
Design and build AI-powered workflows, copilots, and agents that automate and augment Finance processes
Architect and implement systems that integrate across SaaS such as NetSuite, Zip, Zone Advanced Billing, Avalara/Vertex to name a few
Partner with our internal IT AI team and establish best practices for:
Prompt engineering and evaluation
LLM system design and orchestration
Versioning, testing, security, and observability of AI systems
Enable AI Use Cases (copilots, assistants, automated workflows) that drive faster execution and better decision-making for Finance teams
Collaborate with stakeholders to translate business problems into scalable AI solutions
Driving an AI-First Operating Model
Identify high-leverage opportunities to replace manual workflows with AI-native solutions
Define and track success metrics tied to efficiency gains, time savings, and operational effectiveness
Act as a thought partner to Finance leadership on what’s possible with AI, not just what’s requested
Responsible AI, Privacy & Governance: Design systems that handle sensitive financial data with security, privacy, and trust at the core
Partner with Internal Audit, Security, Legal, and Global IT to ensure compliant and ethical AI deployment
Cross-Functional Collaboration & Enablement
Work closely with Security, Global IT, and GTM Systems to align on shared AI infrastructure and standards
Contribute to and adopt company-wide AI patterns, tooling, and best practices
Enable Finance teams to leverage AI by building:
Reusable frameworks and workflows
Playbooks and training materials
Help non-technical stakeholders confidently use and iterate on AI-powered tools
Technical Leadership
Advocate for scalable, well-governed AI systems that integrate cleanly into Klaviyo’s broader tech ecosystem
Act as a key voice in shaping how Klaviyo becomes AI-first internally, starting with Finance systems
What Makes You a Great Fit
Passion and Curiosity to experiment and reimagine Finance workflows
Minimum 5+ years of engineering or data engineering experience, with 2+ years building AI/ML
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