Senior Software Engineer

Senior Software Engineer Recommendations

Boston MA (Hybrid)

What youll do

As the Senior Software Engineer for Product Recommendations you will be a key contributor in building the machine learningpowered systems that decide which products to show to whom and when across all channels powered by our platform. This hands-on backend role focuses on converting billions of behavioral events into personalized product recommendations that drive revenue for merchants. You will define technical direction build and operate services and data pipelines end to end from data ingestion and feature generation to ranking models and APIs.

• Lead the design architecture and operation of backend services that power product recommendations across Klaviyo experiences (email SMS KAgent onsite etc.) upholding standards for reliability performance and clear APIs.
• Architect and maintain robust large-scale data processing pipelines (e.g. using Apache Spark or similar frameworks) that transform raw events and catalog data into high-quality features and inputs for recommendation models ensuring data quality and lineage.
• Collaborate closely with ML engineers and product stakeholders to strategically productionize recommendation modelsdefining high-level interfaces robust feature contracts and advanced deployment patterns for batch and/or real-time inference systems.
• Drive the development of ML/AI systems such as vector search that power recommendation semantic search and sophisticated agentic use cases.
• Implement and evolve data and service observability (metrics logging tracing dashboards) to proactively ensure recommendations are correct fast and highly available for all customers.
• Contribute to and mentor others on shared data frameworks libraries and architectural patterns to accelerate the development of new recommendation use cases and iteration velocity across the team.
• Work with Product to break down projects into clear milestones balancing the need for rapid experimentation with technical soundness and long-term maintainability.
• Lead data-driven decision making and A/B testing effortsensuring recommendation systems are instrumented with the right metrics and independently interpreting results to guide future product and engineering iterations.
• Participate in on-call and incident response for the systems you own driving major post-incident follow-ups that substantially improve the resilience and operability of our recommendation stack.
• Champion and drive the transformation of engineering workflows by integrating AI from the ground upfor example using AI to accelerate development automate complex tests or build smarter monitoring and debugging tools.
• Share knowledge mentor junior/mid-level engineers and define best practices on working with large-scale data frameworks distributed systems and integrating ML into production systems.

Who you are

• 5 years of software engineering experience with experience building and operating mission-critical backend services and systems in a production environment.
• Experience in backend and distributed systems at scale; you have a proven track record working on high-throughput highly available services and are an skilled in optimizing for latency reliability and operability.
• Proficient in Python and open to working in other languages
• Comfortable with cloud-native architectures (AWS preferred) and container orchestration (e.g. Kubernetes); you manage infrastructure and CI/CD pipelines as a core part of your development process.
• Experience in data-driven decision making and A/B testingyou can define how to instrument experiments read and interpret results and ensure learnings are folded back into system design.
• Comfortable designing and querying data models in relational analytical and NoSQL datastores (e.g. Postgres MySQL data warehouses Redis vector databases).
• Feel at home with modern DevOps practices (CI/CD monitoring alerting) and how to apply them to architect large-scale data and recommendation systems.
• Track record of owning multi-component projects end-to-endfrom initial technical design and implementation through rollout monitoring and sustained iteration.
• Excellent technical collaborator and communicator: you can clearly articulate complex technical trade-offs to both technical peers and non-technical partners and you work effectively to drive alignment across ML Engineers Software Engineers PMs and other teams.
• You are a self-starter who has actively experimented with AI in work or personal projects and are excited to responsibly explore and define new AI tools and workflows to enhance team productivity and system intelligence.

Nice to have

• Previous experience working on product recommendation systems or adjacent ML-powered features (ranking personalization search or similar).
• Experience with big data frameworks such as Apache Spark (or similar technologies like Flink Beam etc.) for architecting and building complex batch or streaming pipelines.
• Experience in AI/ML systems and products such as integrating models into production systems building features powered by ML or contributing to the ML infrastructure.
• Experience training and iterating on machine learning models (e.g. for ranking prediction or personalization).
• Experience with ML and distributed compute frameworks such as Ray or similar tools.
• Experience partnering with data science or ML teams to productionize models (designing feature stores ensuring offline/online parity advanced model deployment and monitoring).
• Background in e-commerce marketing tech or consumer personalization products.

We use Covey as part of our hiring and / or promotional process. For jobs or candidates in NYC certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on April 3 2025.

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Required Experience:

Senior IC