Lead AI Engineer

Lead Software AI Engineer

At Klaviyo, we believe the future of software lies not in productivity tools for human users but in software that can run and optimize itself based on outcome or reward metrics. We’ve built the infrastructure and application that serve as the interface between businesses and consumers. We now have over 167,000 customers, billions of consumer profiles, and hundreds of billions of customer messages and follow-on conversion data. We have a big opportunity to build state-of-the-art AI and machine learning technologies at Klaviyo to power our products and develop AI agents that can automatically create and execute marketing or customer experiences, strategies, and campaigns for any business.

As a Lead Software AI Engineer at Klaviyo, you’ll set technical direction and drive the design of scalable backend systems and AI-powered user experiences that form the foundation of our AI product strategy. You’ll work closely with product managers, machine learning engineers, and data scientists while mentoring engineers and shaping architectural decisions. This is a backend-heavy leadership role with a strong focus on applied AI/ML, including large language models (LLMs) and agentic AI systems.

How You Will Make a Difference

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  Lead the design and development of backend systems that enable scalable AI solutions for 167K+ customers.



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  Architect robust, reliable, and scalable data pipelines that train and serve AI/ML models at scale.



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  Drive the integration of LLMs into production systems, powering AI agents that create and execute real-time customer experiences.



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  Establish best practices for model evaluation, monitoring, and performance across generative and agentic AI use cases.



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  Mentor and guide engineers, fostering a culture of technical excellence, ownership, and customer-centric product thinking.



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  Partner with cross-functional leaders to influence AI product strategy and deliver high-impact solutions.

Who You Are

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  7–10 years of professional software engineering experience , with a strong focus on backend systems and distributed architectures.



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  Recent, hands-on experience with AI/ML and LLMs , including fine-tuning, evaluation, and production deployment.



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  Proven ability to design and scale distributed systems that support AI-driven applications and agent capabilities.



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  Proficient in Python and modern backend frameworks (FastAPI, Django preferred).



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  Skilled with big data tools (Apache Spark, Hadoop) and distributed task queues (Kafka, Celery, SQS, RabbitMQ, Redis).



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  Experienced in architecting APIs and cloud-native solutions (AWS, Kubernetes, CI/CD pipelines).



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  Demonstrated technical leadership — mentoring engineers, shaping architecture, and raising the bar for engineering practices.



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  Thrives in a fast-paced, startup-like environment with high autonomy and ownership.



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  Curious, adaptable, and motivated to stay on the cutting edge of AI/ML research and apply it to real-world business challenges.

Nice to Have

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  Experience training and deploying reinforcement learning systems.



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  Prior experience leading cross-functional initiatives involving data science, ML engineering, and product.

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