Staff Engineer - Realtime and Personalization

**About the company:** Treasure Data Minato-ku, Tokyo Treasure Data is the only enterprise Customer Data Platform that harmonizes an organization’s data, insights, and engagement technology stacks to drive relevant, real-time customer experiences throughout the entire customer journey. **Responsibilities:** Drive technical design, specifications, and implementation for the Personalization and Realtime engine. You will build and maintain robust backend APIs using Ruby on Rails and scalable serverless functions using TypeScript on AWS Lambda, MemoryDB and DynamoDB. Architect and refine complex distributed systems on AWS, ensuring they can handle high-throughput real-time data processing with low latency using complex data access patterns using DynamoDB and MemoryDB. Ensure success in our effort to integrate AI Agent creation and execution capabilities into our core platform. You will build the infrastructure that allows agents to act intelligently within the stack. Partner with Product Managers and Engineering Managers in a squad model to deliver projects on time. You will break down complex requirements into executable engineering tasks, and optionally serve as a tech lead for a squad. Elevate the engineers around you. You will mentor Senior and mid-level engineers, modeling best practices in code review, design patterns, and operational excellence. Build with a mind toward scalability, observability, and security. You will join the on-call rotation and treat production operations as a first-class citizen. Requirements 8+ years of software engineering experience, with a proven track record of delivering complex backend systems in production environments. Significant experience writing high-performance Web APIs in frameworks like Ruby on Rails or Kotlin and building serverless applications (bonus points for using TypeScript.) Deep familiarity with AWS (Lambda, API Gateway, Kinesis, DynamoDB, RDS) and experience architecting distributed systems. Experience or strong interest in integrating AI/ML workflows into a backend architecture (e.g., working with LLM APIs, agent orchestration, or personalization engines). You possess deep production experience with DynamoDB and in-memory stores like MemoryDB (Redis). You are comfortable modeling data for high-scale, non-relational access patterns. (Familiarity with SQL patterns is expected, but NoSQL is our primary driver). You have a history of mentoring other engineers, conducting insightful code reviews, and elevating the technical bar of your team. Strong written and verbal communication skills. You are comfortable working with distributed teams across different time zones (specifically bridging North America and Japan) and promoting an async-first workflow. Business-level English proficiency is required. You can effectively communicate complex technical concepts to non-technical stakeholders. Nice to haves While not specifically required, tell us if you have any of the following. Experience with Event-Driven Architectures and real-time data processing. Experience with AI frameworks (LangChain, etc.) from an infrastructure/integration perspective. APPLY FOR THIS POSITION DO YOU NEED MORE INFO? ASK A QUESTION Meet Treasure Data's Developers Scaling ML Algorithms for Enterprise with David Landup David discusses how he enjoys switching hats between ML and software, and why he finds Treasure Data’s “extensive ecosystem” so much fun. Read their story... Overcoming Imposter Syndrome at Treasure Data with Tyler Welsh Tyler is a software engineer at Treasure Data working on their Data Clean Room product. He talks about how Treasure Data supports their team’s learning and growth, and how they invest in the quality and performance of their services. Read their story... **Requirements:** 8+ years of software engineering experience, with a proven track record of delivering complex backend systems in production environments. Significant experience writing high-performance Web APIs in frameworks like Ruby on Rails or Kotlin and building serverless applications (bonus points for using TypeScript.) Deep familiarity with AWS (Lambda, API Gateway, Kinesis, DynamoDB, RDS) and experience architecting distributed systems. Experience or strong interest in integrating AI/ML workflows into a backend architecture (e.g., working with LLM APIs, agent orchestration, or personalization engines). You possess deep production experience with DynamoDB and in-memory stores like MemoryDB (Redis). You are comfortable modeling data for high-scale, non-relational access patterns. (Familiarity with SQL patterns is expected, but NoSQL is our primary driver). You have a history of mentoring other engineers, conducting insightful code reviews, and elevating the technical bar of your team. Strong written and verbal communication skills. You are comfortable working with distributed teams across different time zones (specifically bridging North America and Japan) and promoting an async-first workflow. Business-level English proficiency is required. You can effectively communicate complex technical concepts to non-technical stakeholders. **Nice to have:** While not specifically required, tell us if you have any of the following. Experience with Event-Driven Architectures and real-time data processing. Experience with AI frameworks (LangChain, etc.) from an infrastructure/integration perspective. APPLY FOR THIS POSITION DO YOU NEED MORE INFO? ASK A QUESTION Meet Treasure Data's Developers Scaling ML Algorithms for Enterprise with David Landup David discusses how he enjoys switching hats between ML and software, and why he finds Treasure Data’s “extensive ecosystem” so much fun. Read their story... Overcoming Imposter Syndrome at Treasure Data with Tyler Welsh Tyler is a software engineer at Treasure Data working on their Data Clean Room product. He talks about how Treasure Data supports their team’s learning and growth, and how they invest in the quality and performance of their services. Read their story...