Software Engineer II- Product Recommendations
Quick Summary
At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day.
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…
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.
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.
Boston, MA (Hybrid)
Responsibilities
~2 min readAs 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 productionize 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.
- 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 NoSQL datastores.
- 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.
Nice to Have
~1 min read- Exposure to product recommendation systems or adjacent ML-powered features (ranking, personalization, search, or similar).
- Exposure to big data frameworks such as Apache Spark (or similar technologies like Flink, Beam, etc.) for data pipelines.
- Interest in AI/ML systems and products, such as learning how models are integrated into production systems.
- Background in e-commerce, marketing tech, or consumer personalization products.
What We Offer
~2 min readWe’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.
Location & Eligibility
Listing Details
- First seen
- March 23, 2026
- Last seen
- May 24, 2026
Posting Health
- Days active
- 61
- Repost count
- 0
- Trust Level
- 42%
- Scored at
- May 24, 2026
Signal breakdown

We help businesses of every size — from entrepreneurs to iconic brands.
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