Python Software Engineer (Product Infrastructure)

• Join Corsearch as Python Software Engineer (Product Infrastructure): build reliable, scalable infra powering AI‑driven brand protection for 5,000+ customers worldwide
• We are looking for a Software Engineer to join our Product Infrastructure team
• Our team sits at the critical intersection of raw data collection and product utility
• We focus heavily on infrastructure support, scalability, and service provisioning—ensuring that data flows seamlessly from upstream scrapers, refines through our AI models, and lands reliably into our production application
• Ingestion Pipeline: Own and accelerate our migration from legacy daily tasks to a high‑throughput, real‑time stream processing ingestion pipeline
• Infrastructure Scaling: Manage service provisioning and scaling infrastructure, including expanding our adoption of Kubernetes
• Database Management & Optimization: Ensure database consistency and optimize complex operations, specifically utilizing Postgres, to maintain high performance under heavy resource usage
• Automation: Support and evolve our real‑time auto‑moderation pipeline, collaborating with the Product Engineering team to further develop the feature
• Cross‑Functional Collaboration: Work closely with different squads and various stakeholders. You will directly translate business requirements into technical execution

Proven experience building, deploying and monitoring production‑grade applications. Experience working with relational databases (we use PostgreSQL), including index tuning, query optimization, etc. Outstanding communication skills with the ability to bridge the gap between technical execution and non‑technical stakeholders. Python is our primary backend language, but we are open to strong experience in any core programming language (such as Go, C++, Java, etc.). The most important thing is that you are fully motivated to adapt, learn, and develop primarily in Python moving forward. Solid understanding of cloud computing concepts and hands‑on experience with at least one major cloud provider (we use AWS). Deep understanding of data pipeline architectures, infrastructure systems. Hands‑on experience with Kubernetes management and orchestration. Foundational knowledge or curiosity regarding Artificial Intelligence / Machine Learning integration within data workflows.