Software Engineer, Conversational Products & Agent Workflows

At Klaviyo, we believe the future of software lies not only in tools that help people work efficiently, but in intelligent systems that can take action, learn from outcomes, and improve customer experiences over time. Serving over 167,000 customers and processing billions of consumer profiles and conversion signals, Klaviyo provides a unique environment for building state-of-the-art AI systems at scale.

We are looking for a Software Engineer, Conversational Products & Agent Workflows to join the Customer Agent team—Klaviyo’s AI-native conversational platform. In this backend-heavy role, you will build scalable services and product experiences that enable autonomous agents to retrieve context, execute tools, and carry out reliable multi-step actions on behalf of customers.

Key Responsibilities

• Backend & API Engineering: Build and improve reliable backend services, data pipelines, and REST/gRPC APIs that power AI-driven customer experiences.
• Agentic Features & Workflows: Develop production agentic capabilities involving tool orchestration, context retrieval, structured outputs, and multi-step agent execution.
• Applied AI & RAG: Contribute to solving applied AI challenges across Retrieval-Augmented Generation (RAG), grounding, hallucination mitigation, model selection, and hybrid/deterministic logic vs. LLM execution.
• Evaluation & Quality: Build and apply evaluation suites using representative datasets, automated/human feedback, regression testing, and production quality signals.
• System Reliability: Implement production guardrails, fallbacks, retry policies, observability metrics, and failure-handling mechanisms for agentic features.
• Distributed Workflows: Engineer asynchronous processing workflows and distributed task queues capable of handling high-volume AI workloads.
• Operations & Customer Feedback: Participate in the team on-call rotation to mitigate production incidents, and engage with external customers to translate operational feedback into feature improvements.

Requirements

Experience & Education

• 3+ years of professional software engineering experience, with a focus on backend development or distributed applications.
• Hands-on experience building or contributing to generative AI or agentic AI applications (ideally used by real users or in production environments).

Technical Capabilities

• Proficiency in Python and experience with modern backend frameworks (e.g., FastAPI, Django).
• Practical experience with asynchronous task processing and event-driven systems (Celery, Kafka, AWS SQS, RabbitMQ, or Redis).
• Working knowledge of database modeling, SQL/NoSQL persistence patterns, and API architecture.
• Comfort operating in cloud-native environments (AWS, Docker/containers, Kubernetes, infrastructure automation, CI/CD pipelines).
• Ability to evaluate technical tradeoffs across quality, latency, cost, reliability, and architectural complexity.

Preferred Qualifications

• Experience training, fine-tuning, distilling, or adapting machine learning and language models for production workflows.
• Hands-on experience with reinforcement learning or feedback-driven optimization techniques.
• Exposure to evaluation infrastructure (e.g., LLM-as-judge frameworks, evaluator calibration, benchmark datasets, AI quality tooling).
• Experience operating AI systems at scale or optimizing inference cost, latency, or throughput.