Director of Engineering, AI

Klaviyo•Boston, MA

About The Position

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’s mission is to help businesses own their growth. AI is at the center of that mission — and we’re building the engineering organization to match. As Director, Engineering – AI, you’ll lead the teams turning our AI strategy into real, daily leverage for hundreds of thousands of customers: from the underlying AI platform and agent framework to the product experiences embedded throughout Klaviyo. You’ll own the technical vision and execution strategy for AI-powered capabilities across Klaviyo’s product surface, partnering deeply with Product, Design, ML, Data Science, and GTM to define what to build, ship it quickly and safely, and measure real impact in customer outcomes — not just model demos. This is a hands-on, execution-first role for a product-minded engineering leader who is fluent in modern LLMs, agent patterns, and what it takes to bring AI capabilities to production at scale.

Requirements

An experienced, product-minded engineering leader. ~10+ years in software engineering, including 5+ years leading multiple teams and managers building user-facing products in high-growth SaaS or similar environments. You’re energized by building things customers love, not just infrastructure for its own sake.
Hands-on with modern AI and agentic systems. You’ve led teams building with LLMs, retrieval-augmented generation, or agent frameworks — designing multi-step flows, tool calling, memory, evaluation, and safety guardrails — even if you’re not coding every day.
A deep systems and product thinker. You can dive into architecture and data flows, but also reason from first principles about customer workflows, jobs-to-be-done, and where AI can produce step-change improvements vs. incremental shortcuts.
An outcome-oriented operator. You define clear success metrics and hold teams accountable to them; you’re comfortable saying “no,” narrowing scope, and iterating fast.
A builder of high-performing, inclusive teams. You’ve hired and developed diverse engineering teams, grown new leaders, and created cultures where people do the best work of their careers while feeling respected and included.
An exceptional collaborator and communicator. You translate complex AI/ML and systems topics into clear narratives for non-technical partners; you influence peers and executives, drive alignment across Product, Engineering, Data, and GTM, and model Klaviyo’s values in how you work.
Adaptable and resilient. You stay close to the work, dive deep when needed, and lead your teams through ambiguity and change with clarity and calm.
A practitioner of AI-first ways of working. You know how to lead your whole team to use AI in day-to-day engineering development cycles, and you’ve experimented with or practiced fully agentic coding workflows.
You’ve already experimented with AI in work or personal projects, and you’re excited to dive in and learn fast. You’re hungry to responsibly explore new AI tools and workflows, finding ways to make your work smarter and more efficient.

Nice To Haves

Experience building AI-powered products for end users in complex SaaS workflows (e.g., martech, CRM, growth tooling, developer platforms).
Prior work on agentic or copilot-style experiences embedded in production products at scale.
Background combining experimentation platforms, offline evaluation, and human review loops to improve AI systems over time.
Experience operating in multi-product, multi-team environments where clear interfaces and ownership boundaries are critical.
Comfort working from our Boston hub with distributed teams across time zones.

Responsibilities

Own the AI engineering charter. Define the technical vision and roadmap for AI-powered capabilities on Klaviyo’s platform, and translate it into clear plans, OKRs, and milestones for your teams.
Design and evolve the AI platform. Lead the architecture for LLM-powered and agentic systems — orchestration, tool/function calling, retrieval and memory, evaluation harnesses, observability, and safety guardrails tuned for real-world product workflows.
Ship remarkable, AI-native product experiences. Partner with Product, Design, and partner engineering teams to prioritize the highest-value use cases, break them into shippable iterations, and launch experiences that feel intuitive and powerful — not just demos bolted onto existing UI.
Make safety, reliability, and measurability non-negotiable. Define success metrics and guardrails for AI systems (e.g., time-to-first-value, uplift over baselines, override rates, hallucination/error rates, latency, SLOs), and build the tooling to monitor and continuously improve them in production.
Integrate deeply with Klaviyo’s data and platform stack. Collaborate with Data Platform, Production Infrastructure, and product engineering teams to ensure AI systems can safely and efficiently access the right data while respecting privacy, security, and governance constraints.
Raise the bar on AI engineering craft. Build shared patterns, libraries, and best practices for prompt and chain design, evaluation, human-in-the-loop review, and observability that other teams can reuse; champion rigorous experimentation, A/B testing, and fast feedback loops.
Lead high-performing engineering teams (ICs and managers). Hire, develop, and retain high-performing, inclusive teams; set crisp expectations, coach for impact, and create a culture of urgency, accountability, and psychological safety.
Partner across Klaviyo to land changes. Work closely with GTM, Support, and Customer Success to roll out new AI capabilities safely, enable the field, and close the loop between customer feedback, product decisions, and system improvements.
Measure what matters. Own a clear scorecard for your area — adoption, activation, uplift vs. baselines, quality/satisfaction, AI system reliability, and developer velocity — and use it to drive prioritization and investment decisions.
Transform workflows by putting AI at the center, building smarter systems and ways of working from the ground up, and continuously experimenting with AI tools — testing, learning, and sharing insights to keep Klaviyo ahead of the curve.