Senior Software Engineer, Agent Runtime & Customer Workflows

Klaviyo • Boston, MA

22h

About The Position

Klaviyo is seeking a Senior Software Engineer to join its Customer Agent team, an AI-native conversational platform. The role focuses on designing and building scalable backend systems and AI-powered product experiences that let agents reason, retrieve context, use tools, and take reliable action on customers’ behalf. The engineer will independently own significant technical problems, make pragmatic engineering tradeoffs, and help evolve the architecture and quality of these systems.

The position involves developing production agentic systems and workflows, addressing applied AI challenges, creating evaluation strategies, and improving reliability. The engineer will collaborate with external customers and cross-functional partners to understand workflows and pain points, then use customer feedback and product signals to improve shipped experiences. The role also participates in an on-call rotation and supports diagnosis and mitigation of production incidents.

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 persistence patterns used in production systems.
• Comfort working in cloud-native environments with technologies such as 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, break down loosely defined problems, and make pragmatic decisions about what to build first.
• Experience with and genuine interest in working directly with external customers to understand problems and improve products.
• Care for shipping useful, reliable products, with curiosity and sound engineering judgment in a rapidly evolving technical space.

Nice To Haves

• Experience training, fine-tuning, distilling, or otherwise adapting machine learning or language models for production use.
• Experience with reinforcement learning or feedback-driven optimization.
• Experience building evaluation infrastructure such as LLM-as-judge systems, evaluator calibration frameworks, benchmark suites, or AI quality platforms.
• Experience operating AI systems at substantial scale, including optimizing inference cost, latency, or throughput.

Responsibilities

• Design and build reliable, scalable backend systems and APIs for AI-driven customer experiences.
• Build and evolve production agentic systems involving tool use, orchestration, context management, retrieval, structured outputs, and multi-step workflows.
• Address applied AI problems involving retrieval and RAG, grounding, model selection, hallucination mitigation, and choosing deterministic or hybrid approaches where appropriate.
• Develop evaluation strategies using representative datasets, automated and human evaluation, regression testing, qualitative error analysis, and production signals.
• Improve production reliability through guardrails, fallbacks, retries, observability, monitoring, and thoughtful failure handling.
• Build asynchronous and distributed processing workflows for high-volume AI workloads.
• Participate in an on-call rotation and help diagnose, mitigate, and learn from production incidents.
• Work with external customers and cross-functional partners to understand workflows, identify pain points, and translate feedback into product and technical improvements.
• Monitor shipped experiences and use customer behavior, quality metrics, and system performance to guide iteration.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed