2 days ago
Base Salary
$148k - $222k/yr
Responsibilities
- Design and build reliable, scalable backend systems and APIs for AI-driven customer experiences.
- Develop production agentic systems involving tool use, orchestration, context management, retrieval, structured outputs, and multi-step workflows.
- Solve applied AI problems involving RAG, grounding, model selection, hallucination mitigation, and deterministic or hybrid approaches.
- Create evaluation strategies using representative datasets, automated and human evaluation, regression testing, qualitative error analysis, and production signals.
- Improve reliability through guardrails, fallbacks, retries, observability, monitoring, and failure handling.
- Build asynchronous and distributed workflows for high-volume AI workloads.
- Participate in on-call rotations and diagnose, mitigate, and learn from production incidents.
- Work with external customers and cross-functional partners to identify workflow problems and translate feedback into product improvements.
- Monitor shipped experiences and use customer behavior, quality metrics, and system performance to guide iteration.
Requirements
- 5–7 years of professional software engineering experience with a strong foundation in backend systems and distributed applications.
- Hands-on experience building and deploying generative AI or agentic AI applications into production for real users.
- Proficiency in Python and modern backend frameworks such as FastAPI or Django.
- Experience with asynchronous processing and distributed task or event systems such as Celery, Kafka, SQS, RabbitMQ, or Redis.
- Strong knowledge of databases, data modeling, APIs, and production persistence patterns.
- Comfort working in cloud-native environments with AWS, containers, Kubernetes, infrastructure automation, or CI/CD systems.
- Ability to reason about tradeoffs among quality, latency, cost, reliability, and implementation complexity.
- Ability to work independently in ambiguous environments and make pragmatic prioritization decisions.
- Experience and interest in working directly with external customers.
- Preferred experience training, fine-tuning, distilling, or adapting machine learning or language models for production use.
- Preferred experience with reinforcement learning, feedback-driven optimization, LLM-as-judge systems, evaluator calibration, benchmark suites, AI quality platforms, or operating AI systems at scale.
Benefits
- Base compensation is supplemented by potential annual cash bonus, variable compensation where applicable, equity, sign-on payments, and health, welfare, and wellbeing benefits based on eligibility.
- The role may require up to 10% travel for onboarding, client or partner work, team meetings, and industry events, with travel coordinated in advance.
- Klaviyo provides accommodations as needed and supports an equal-opportunity workplace.
Tech Stack
Categories
About Klaviyo
Klaviyo builds a subscription SaaS platform that lets e-commerce and consumer brands use first-party data to run targeted email, SMS, and push campaigns, with built-in automation and analytics. The product also includes B2C CRM features for segmentation, A/B testing, and customer lifecycle workflows. Founded in 2012 and headquartered in Boston, it is a public company (NYSE: KVYO) used by brands such as Mattel and Glossier.