Klaviyo
Want to learn more about life at Klaviyo?
Visit careers.klaviyo.com to see how we empower creators to own their own destiny.
Pick a job to read the details
Tap any role on the left — its description and apply link will open here.
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.
Job Title: Lead AI Engineer – Marketing & Service AI
Location: Palo Alto, CA
This role is based in our new Palo Alto hub. We operate a hub‑first model, with regular in‑office collaboration expected.
About the Role
At Klaviyo, we believe the future of software isn’t just better productivity tools for humans—it’s systems that can run, optimize, and adapt themselves based on outcome and reward signals. We’ve already built the infrastructure and applications that sit between businesses and consumers—serving 183,000+ customers, billions of consumer profiles, and hundreds of billions of messages and conversion events. Now we’re investing heavily in Marketing AI and Service AI: the shared services and agentic capabilities that power AI‑native experiences across Klaviyo.
As a Lead AI Engineer in the AI & Analytics organization, you’ll play a key role in designing and building scalable backend systems and user experiences that power our AI products and agentic solutions. You’ll own complex services end‑to‑end, contribute to architecture for high‑impact AI features, and partner closely with product managers, machine learning engineers, and data scientists to turn AI ideas into reliable, scalable production capabilities. This is a hands‑on, backend‑heavy role with opportunities to influence architecture, async processing pipelines, distributed systems, and more—without being the overall area tech lead.
You’ll be based in our new Palo Alto office, a center of gravity for AI at Klaviyo—surrounded by teammates with deep ML and AI experience, and tightly connected to our other U.S. and international R&D hubs. You’ll collaborate daily with engineers in Boston and other locations, and you’ll have a clear path to grow into broader technical leadership, staff/principal scope, or future people leadership if that’s the direction you want to go—without being constrained by hub location.
How You’ll Make a Difference
- Design and build core AI services. Implement scalable, low‑latency backend systems and APIs that power our Marketing and Service AI capabilities for 183K+ customers, handling billions of events and interactions.
- Scale AI data and inference pipelines. Develop robust, reliable, and scalable data collection and processing pipelines so our generative and agentic models have the features, context, and feedback they need to perform well in production.
- Build and harden AI serving systems. Implement services that host and orchestrate AI models (LLMs, tools, evaluators, retrieval systems), with strong contracts, logging, and observability so other teams can depend on them.
- Evolve our agentic architecture. Help evolve how our agents plan, call tools, and react to feedback—shipping improvements that increase autonomy, reliability, and safety for both customer‑facing and internal workflows.
- Apply and refine best practices for AI systems. Use and help improve standards for evaluation, safety/guardrails, prompt and model management, offline/online tests, and incident response for AI‑backed systems.
- Collaborate across teams. Work closely with product, ML, data, and platform teams to clarify requirements, align on interfaces, and unblock dependencies for the services you own—especially across hubs and time zones.
- Mentor and uplevel teammates. Provide thoughtful code reviews, share patterns and examples, and help mid-level and junior engineers grow stronger in building distributed and AI‑powered systems.
- Help shape the Palo Alto hub. Participate in interviewing, onboarding, and local engineering rituals; contribute ideas that make Palo Alto a highly collaborative, high‑bar hub that works seamlessly with other locations.
- Measure what matters. Instrument your services and use metrics—availability, latency, cost‑to‑serve, agent success rates, eval scores, and customer adoption—to guide your own technical decisions and influence the team roadmap.
- You’ve already been effectively practicing agentic coding in your daily work. You’re hungry to responsibly explore new AI tools and workflows, finding ways to make your work smarter and more efficient.
Who You Are
- Experienced backend engineer. 5–7+ years of professional software engineering experience with a strong focus on backend and distributed systems; you’ve led complex projects end‑to‑end within a team and owned services in production.
- Hands‑on with generative & agentic AI in production. You’ve built and shipped generative or agentic AI applications (e.g., LLM‑backed flows, tool‑using agents, retrieval‑augmented systems) and are comfortable with prompt design, few‑shot approaches, fine‑tuning, and evaluation.
- Strong distributed systems and async background. You’ve built reliable services, async processing pipelines, and distributed task queues (e.g., Celery, Kafka, SQS, RabbitMQ, Redis) that support high‑throughput workloads.
- Fluent in Python and data tooling. Proficient in Python and modern backend frameworks (FastAPI, Django or similar), with experience using big data tools such as Spark/Hadoop and ORMs like SQLAlchemy/Alembic.
- Comfortable in cloud‑native environments. Experience with AWS and Kubernetes, CI/CD pipelines, observability, and operational best practices; you understand how infrastructure choices affect reliability, latency, and cost.
- Evaluation and quality‑minded. You’ve created human and/or automated evals for AI systems, instrumented for quality, and understand how to balance latency, cost, and response quality in real‑world usage.
- Collaborative and customer‑first. You enjoy working directly with PMs, engineers in other teams, and sometimes customers; you care deeply about the customer experience and use data and feedback to guide decisions.
- Growth‑oriented teammate. You communicate clearly, give and receive feedback well, and contribute to a team culture that is humble, ambitious, and values‑aligned.
- 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.
- You’ve already been effectively practicing agentic coding in your daily work—or you’re eager to deepen that practice—using AI assistants and tools to scaffold code, run experiments, and iterate faster while keeping yourself in the driver’s seat.
- Bonus: You use AI tools to accelerate exploration, shorten iteration cycles, and bring sharper ideas to the table—for yourself and your teammates.
Nice to Haves
- Prior experience training and deploying your own ML models (including RL or RLHF) into production systems that drove measurable business impact.
- Experience building shared AI/ML platforms or services used by multiple product teams.
- Background in marketing tech, ecommerce, or other domains where customer data, personalization, and experimentation are central.
We use Covey as part of our hiring and / or promotional process. For jobs or candidates in NYC, certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on April 3, 2025.
Please see the independent bias audit report covering our use of Covey here
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.
In addition to base salary, our total compensation package may include participation in the company’s annual cash bonus plan, variable compensation (OTE) for sales and customer success roles, equity, sign-on payments, and a comprehensive range of health, welfare, and wellbeing benefits based on eligibility.
Your recruiter can provide more details about the specific salary/OTE range for your preferred location during the hiring process.
This role may require up to 10% travel for purposes such as new hire onboarding, client or partner work if applicable, team meetings, and industry events. Travel is coordinated in advance.
Get to Know Klaviyo
We’re Klaviyo (pronounced clay-vee-oh). We empower creators to own their destiny by making first-party data accessible and actionable like never before. We see limitless potential for the technology we’re developing to nurture personalized experiences in ecommerce and beyond. To reach our goals, we need our own crew of remarkable creators—ambitious and collaborative teammates who stay focused on our north star: delighting our customers. If you’re ready to do the best work of your career, where you’ll be welcomed as your whole self from day one and supported with generous benefits, we hope you’ll join us.
AI fluency at Klaviyo includes responsible use of AI (including privacy, security, bias awareness, and human-in-the-loop). We provide accommodations as needed.
By participating in Klaviyo’s interview process, you acknowledge that you have read, understood, and will adhere to our Guidelines for using AI in the Klaviyo interview Process. For more information about how we process your personal data, see our Job Applicant Privacy Notice.
Klaviyo is committed to a policy of equal opportunity and non-discrimination. We do not discriminate on the basis of race, ethnicity, citizenship, national origin, color, religion or religious creed, age, sex (including pregnancy), gender identity, sexual orientation, physical or mental disability, veteran or active military status, marital status, criminal record, genetics, retaliation, sexual harassment or any other characteristic protected by applicable law.
Ready to apply?
Apply to Klaviyo
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.
Job Title: Sr. Lead AI Engineer
Location: Palo Alto, CA
This role is based in our new Palo Alto hub. We operate a hub‑first model, with regular in‑office collaboration expected.
About the Role
At Klaviyo, we believe the future of software isn’t just better productivity tools for humans—it’s systems that can run, optimize, and adapt themselves based on outcome and reward signals. We’ve already built the infrastructure and applications that sit between businesses and consumers—serving 183,000+ customers, billions of consumer profiles, and hundreds of billions of messages and conversion events. Now we’re investing heavily in Marketing AI and Service AI: the shared services and agentic capabilities that power AI‑native experiences across Klaviyo.
As a Sr. Lead AI Engineer in the AI & Analytics organization, you’ll be the technical leader for a set of high‑impact AI services and agentic systems. You’ll own architecture and execution for complex, distributed backend systems; guide other engineers through design and implementation; and partner closely with product, machine learning, and data science to turn AI ideas into reliable, scalable production capabilities. This is a hands-on tech lead role, not a people‑manager role.
You’ll also be located in our new Palo Alto office. This hub is a center of gravity for AI at Klaviyo—with employees in this hub all having machine learning and AI knowledge and experiences, but also tightly connected to our other U.S. and international R&D hubs. You’ll help shape how Palo Alto collaborates with Boston and global teams, and open up clear paths for growth into broader technical leadership, staff/principal‑level scope, or future people leadership if that’s the direction you want to go.
How You’ll Make a Difference
- Define and improve the engineering architecture for Service and Marketing AI capabilities. Lead the design of scalable, low‑latency backend systems and APIs that power our AI products and agents for 183K+ customers, handling billions of events and interactions.
- Build and harden AI serving systems. Lead the development of services that host and orchestrate AI models (LLMs, tools, evaluators, retrieval systems), with clear contracts, SLOs, and observability so other teams can depend on them.
- Evolve our agentic architecture. Drive the technical roadmap for Service and Marketing AI agents—improving tool use, autonomy, and reliability so agents can safely take actions on behalf of customers and internal users with minimal human intervention.
- Set engineering standards for AI services. Establish best practices for evaluation, safety/guardrails, prompt and model versioning, offline and online tests, and incident response for AI‑backed systems; hold the bar for design reviews and code quality.
- Lead cross‑team technical work. Act as the primary technical interface between Service / Marketing AI and other product/platform teams—clarifying ownership boundaries, aligning on interfaces, and unblocking dependencies across hubs and time zones.
- Mentor and uplevel engineers. Coach senior and mid‑level engineers through design, implementation, and operational best practices, helping them grow into stronger system owners and future tech leads.
- Help build the Palo Alto hub. Shape local engineering rituals, help with hiring and onboarding, and create healthy patterns for cross‑hub collaboration so work and career opportunities are not constrained by geography.
- Measure what matters. Define and track key metrics for your systems—availability, latency, cost‑to‑serve, agent success rates, eval scores, and customer adoption—and use those insights to drive roadmap and technical decisions.
- Transform engineering and product development workflows by putting AI at the center, building & utilizing agentic coding tools and AI-first working.
Who You Are
- Seasoned backend engineer & tech lead. ~8+ years of professional software engineering experience with a strong focus on backend and distributed systems; you’ve led complex projects or areas end‑to‑end and acted as the go‑to technical owner for key services.
- Hands‑on with generative & agentic AI in production. You’ve built and shipped generative or agentic AI applications (e.g., LLM‑backed flows, tool‑using agents, retrieval‑augmented systems) and are comfortable with prompt design, few‑shot approaches, fine‑tuning, and evaluation.
- Deep experience with large‑scale distributed systems. You’ve architected and operated reliable services, async processing pipelines, and distributed task queues (e.g., Celery, Kafka, SQS, RabbitMQ, Redis) supporting high‑throughput workloads.
- Strong Python and data tooling fluency. Proficient in Python and modern backend frameworks (FastAPI, Django or similar), with experience using big data tools such as Spark/Hadoop and ORMs like SQLAlchemy/Alembic.
- Production‑grade cloud experience. Comfortable with AWS and Kubernetes, CI/CD pipelines, observability, and operational best practices; you treat infrastructure choices as part of the system design, not an afterthought.
- Evaluation and quality‑obsessed. You’ve designed human and automated evals for AI systems, know how to instrument for quality, and understand how to balance latency, cost, and response quality in real‑world usage.
- Technical leader, not just individual contributor. You influence architecture beyond your own code, facilitate design reviews, rally cross‑functional partners, and help teams converge on pragmatic decisions in ambiguous spaces.
- Collaborative and customer‑first. You’re comfortable collaborating directly with PMs, ML engineers, and customers; you can translate between customer needs, product goals, and technical constraints, and you care deeply about the customer experience.
- You’ve already been effectively practicing agentic coding in your daily work. You’re hungry to responsibly explore new AI tools and workflows, finding ways to make your work smarter and more efficient.
- Bonus: You use AI tools to accelerate exploration, shorten iteration cycles, and bring sharper ideas to the table—for yourself and your teammates.
Nice to Haves
- Prior experience training and deploying ML models (including RL or RLHF) into production systems that drove measurable business impact.
- Experience building shared AI/ML platforms or services used by multiple product teams.
- Background in marketing tech, ecommerce, or other domains where customer data, personalization, and experimentation are central.
We use Covey as part of our hiring and / or promotional process. For jobs or candidates in NYC, certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on April 3, 2025.
Please see the independent bias audit report covering our use of Covey here
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.
In addition to base salary, our total compensation package may include participation in the company’s annual cash bonus plan, variable compensation (OTE) for sales and customer success roles, equity, sign-on payments, and a comprehensive range of health, welfare, and wellbeing benefits based on eligibility.
Your recruiter can provide more details about the specific salary/OTE range for your preferred location during the hiring process.
This role may require up to 10% travel for purposes such as new hire onboarding, client or partner work if applicable, team meetings, and industry events. Travel is coordinated in advance.
Get to Know Klaviyo
We’re Klaviyo (pronounced clay-vee-oh). We empower creators to own their destiny by making first-party data accessible and actionable like never before. We see limitless potential for the technology we’re developing to nurture personalized experiences in ecommerce and beyond. To reach our goals, we need our own crew of remarkable creators—ambitious and collaborative teammates who stay focused on our north star: delighting our customers. If you’re ready to do the best work of your career, where you’ll be welcomed as your whole self from day one and supported with generous benefits, we hope you’ll join us.
AI fluency at Klaviyo includes responsible use of AI (including privacy, security, bias awareness, and human-in-the-loop). We provide accommodations as needed.
By participating in Klaviyo’s interview process, you acknowledge that you have read, understood, and will adhere to our Guidelines for using AI in the Klaviyo interview Process. For more information about how we process your personal data, see our Job Applicant Privacy Notice.
Klaviyo is committed to a policy of equal opportunity and non-discrimination. We do not discriminate on the basis of race, ethnicity, citizenship, national origin, color, religion or religious creed, age, sex (including pregnancy), gender identity, sexual orientation, physical or mental disability, veteran or active military status, marital status, criminal record, genetics, retaliation, sexual harassment or any other characteristic protected by applicable law.
Ready to apply?
Apply to Klaviyo