Director, Application Engineering

About the team

Klaviyo’s Global IT team — part of Global Technology Solutions (GTS) — powers the systems, tools, and infrastructure that keep the company moving fast. We build automation, platforms, and tooling that enable scalability, security, and employee productivity.

The AI & DevOps Engineering team is responsible for delivering the platforms and services that support Klaviyo’s internal use of AI and corporate stack automation. This includes secure LLM integrations, prompt APIs, CI/CD tooling, infrastructure-as-code, and systems that bridge the needs of IT, Security, and R&D. Our goal is to make internal operations smarter, faster, and more reliable through modern engineering practices and emerging technology.

About the role (you)

As the Director of AI & DevOps Engineering, you’ll lead a team of engineers focused on building and operating core internal platforms that support intelligent systems and developer velocity. You’ll define strategy, prioritize roadmap, and partner closely with teams across Klaviyo to operationalize AI tooling and modernize infrastructure.

This role owns both the deployment and management of AI tools (e.g. ChatGPT, Claude, Gemini, Glean) and the development of internal DevOps systems (CI/CD, automation, monitoring, infrastructure provisioning). You’ll deliver shared services that empower internal teams to work more efficiently and focus on solving high-value problems.

How you’ll have an impact

• Lead the engineering roadmap for internal AI platform services, DevOps automation, and infrastructure tooling.
• Build and scale developer tools such as CI/CD pipelines, container orchestration, GitHub integrations, and infrastructure-as-code.
• Partner with Engineering, Security, and Data teams to integrate LLMs and AI services in a safe, scalable way.
• Stand up and support AI services: vector search, internal plugins, prompt orchestration layers, and secure API routing.
• Enable teams across Klaviyo to integrate AI into workflows by supporting pilots, building SDKs, and maintaining internal knowledge bases.
• Drive systems automation for IT services—e.g., identity provisioning, SaaS lifecycle management, endpoint posture, and reporting.
• Mentor and grow a high-performing team of engineers with a focus on technical depth, quality delivery, and service ownership.
• Represent Global IT in technical steering conversations with R&D, Product Infrastructure, and SecOps.
• Transform workflows by putting AI at the center, building smarter systems and ways of working from the ground up.

What we’re looking for

• 10+ years of experience in infrastructure, DevOps, platform engineering, or enterprise IT systems.
• At least 3+ years leading technical teams in high-growth or scaled organizations.
• Proven experience designing and operating CI/CD systems, infrastructure-as-code (Terraform or similar), and observability stacks.
• Familiarity with integrating AI services or LLM APIs into business systems (e.g., OpenAI, Anthropic, Google Gemini, Glean).
• Strong understanding of platform scalability, service reliability, and engineering lifecycle automation.
• Experience managing cloud infrastructure (AWS, GCP), container orchestration (Kubernetes, ECS), and developer platforms.
• Ability to drive cross-functional collaboration and communicate technical priorities to both engineering and non-technical stakeholders.
• A pragmatic and systems-thinking mindset—you look for patterns and build for scale.
• 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 have

• Experience building internal developer platforms (IDPs) or platform-as-a-service environments.
• Understanding of secure LLM patterns: embeddings, vector DBs, prompt injection defense, etc.
• Familiarity with scripting languages (Python, TypeScript, Bash) and automation frameworks.
• Exposure to enterprise SaaS management (Trelica, ConductorOne), endpoint MDM (Jamf, Intune), and RBAC tooling (Okta, GWS).
• Knowledge of RAG pipelines, LangChain, or Weaviate for internal AI workflows.
• Past experience with cost optimization and performance tuning at the infrastructure layer.

**Massachusetts Applicants:**It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Our salary range reflects the cost of labor across various U.S. geographic markets. The range displayed below reflects the minimum and maximum target salaries for the position across all our US locations. The base salary offered for this position is determined by several factors, including the applicant’s job-related skills, relevant experience, education or training, and work {#location}.