Source description
About the role
About SellerMate AI SellerMate is an AI-powered advertising and analytics platform for Amazon sellers and brands. We bring together data from across the Amazon ecosystem — Ads, Seller & Vendor Central, and DSP — and process it at scale to power automation, insights, and an AI agent that helps run our customers campaigns. About the role We're looking for a backend-heavy full-stack engineer to build and scale the data pipelines at the core of our product. You'll work on how we sync, process, and serve large volumes of Amazon data — including a major project to unify and improve our account sync system. You'll own features end to end, primarily on the backend, while being comfortable touching the frontend when needed. Responsibilities Build and maintain backend services on AWS (Lambda, ECS, SQS, S3). Design reliable data pipelines that handle queues, retries, scheduling, and large data volumes. Integrate with Amazon APIs (Ads, SP-API), handling authentication, pagination, and rate limits. Work with MongoDB, including schema design, queries, and performance tuning. Build and maintain REST/GraphQL APIs in Python/Flask that power our app and AI features. Help improve our tooling, deployments, and overall system reliability. Qualifications 4+ years of backend engineering experience. Strong Python skills. Hands-on experience with AWS (Lambda, SQS, S3, or similar). Experience with queue-based / asynchronous systems and data pipelines. Comfortable working with MongoDB or a similar database at scale. Solid REST API design with a Python framework (Flask, FastAPI, or Django). Able to work independently and ship to production. Nice to have Experience with the Amazon Advertising API or SP-API. Familiarity with data lake / analytics tools (Athena, S3, Parquet). GraphQL experience. Frontend skills with React / TypeScript. Infrastructure as code (AWS SAM, CloudFormation, or Terraform). Background in e-commerce, adtech, or analytics.