Software Engineer; Product Recommendations

Requirements

• Relevant Bachelor’s degree in Computer Science or a related field, with 3+ years of relevant industry experience building and operating mission-critical backend services and systems in a production environment
• Foundational understanding of backend and distributed systems concepts
• Experience in backend and distributed systems at scale; you have a proven track record working on high-throughput, highly available services and skilled in optimizing for latency, reliability, and operability
• Proficient in Python and open to working in other languages
• Familiarity with cloud-native architectures (AWS preferred) and established development practices like CI/CD and container orchestration (e.g., Kubernetes)
• Ability to work with existing data models and query relational, analytical, and No
  
  SQL data stores
• Excited about agentic coding, possibly already writing most code agentically
• Demonstrates sound development practices, following established quality guidelines
• Able to openly receive and make changes based on feedback and critique
• Has the drive for continuous learning about Klaviyo and industry practices, patterns, tools, languages, and processes
• (Desirable) Exposure to product recommendation systems or adjacent ML-powered features (ranking, personalization, search, or similar)
• (Desirable) Exposure to big data frameworks such as Apache Spark (or similar technologies like Flink, Beam, etc.) for data pipelines
• (Desirable) Interest in AI/ML systems and products, such as learning how models are integrated into production systems
• (Desirable) Background in e-commerce, marketing tech, or consumer personalization products
• 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

• As a Software Engineer II for Product Recommendations, you will be focused on learning Klaviyo’s systems and delivering production features within the machine learning–powered systems that decide which products to show to whom and when across all channels
• This primarily backend role focuses on reliably implementing solutions to convert behavioral events into personalized product recommendations that drive revenue for merchants and maintaining other systems owned by the team
• You will work with the team to execute on assigned work and maintain systems end to end, with an eye towards growing your ownership and technical ability over time
• Execute and deliver feature work autonomously on backend services that power product recommendations across Klaviyo experiences (email, SMS, KAgent, onsite, etc.), contributing to standards for reliability and performance
• Own features end-to-end, working with product to define requirements, decomposing the problem into discrete pieces of work, delivering, and monitoring for impact
• Contribute to the implementation and maintenance of data processing pipelines (e.g., using Apache Spark or similar frameworks) that transform raw events and catalog data
• Collaborate with ML engineers and product stakeholders to implement changes needed to product ionize recommendation models
• Implement and maintain service observability (metrics, logging, tracing) to ensure recommendations are correct and highly available
• Contribute to team documentation and actively participate in team activities and processes
• Participate in incidents for systems your team owns and assist on-call responders
• Proactively communicate with the team, ask for help as appropriate, and learn from input