Backend Tech Lead — Product Infrastructure

Join Corsearch as Tech Lead: guide a talented team, scale real-time data infrastructure, and shape AI-powered systems that help protect brands and consumers worldwide. We are looking for a Tech Lead to guide and scale our Product Infrastructure team. In this role, you will lead a team of 3–5 engineers while remaining closely involved in technical architecture and execution.

Responsibilities

Manage, mentor, and support a core team of 3–5 engineers; Drive project planning, sprint execution, and technical delivery; Lead and accelerate migration from legacy daily batch tasks to high-throughput real-time stream processing ingestion pipeline; Oversee infrastructure scaling including Kubernetes on AWS and take technical ownership of PostgreSQL performance, index tuning, and database consistency under heavy load; Partner with Product Engineering to evolve real-time auto-moderation pipeline and integrate AI/ML models into core data workflows; Leverage observability stack powered by ClickHouse and Grafana to automate incident investigation, drive performance improvements, and resolve critical bugs; Work with cross-functional squads, product managers, and engineering leaders to translate business objectives into technical roadmaps

Requirements

Direct people management experience OR a strong background in technical leadership, mentoring engineers, or leading project virtual teams (v-teams), with the desire and capability to step into managing 3–5 direct reports; Proven track record building, scaling, and monitoring production-grade backend and infrastructure applications; Python is our primary backend language - welcome candidates with strong experience in other core languages (Go, Java, C++, etc.), provided fully motivated to develop primarily in Python moving forward; Deep hands-on experience with relational databases (specifically PostgreSQL), including query optimization, index tuning, high-concurrency performance tuning and data modelling; Hands-on experience with Kubernetes management, deployment, and container orchestration; Solid understanding of cloud computing concepts with hands-on experience in AWS; Outstanding communication skills with proven ability to bridge complex technical execution with non-technical business stakeholders

Nice to have

Experience architecting or migrating legacy batch systems to real-time streaming data pipelines; Foundational knowledge or practical experience integrating Artificial Intelligence / Machine Learning models into production data workflows