Lead Backend Engineer (Go)

We are building the next generation of our Demand-Side Platform (DSP), enabling advertisers to access premium digital inventory through high-performance programmatic technology.

Our bidder is at the heart of the platform, making real-time auction decisions and powering global advertising campaigns. We are looking for a Lead Backend Engineer (Go) to shape its architecture, performance, and future direction, while driving technical quality and helping grow the engineering team.

• Extensive experience in backend software development with Go;
• Strong understanding of distributed systems and microservice architectures;
• Experience building and operating high-performance, low-latency backend services;
• Proven ability to identify, analyze, and resolve complex performance and scalability challenges;
• Ability to work independently and drive initiatives from concept to production;
• Strong communication skills and experience working closely with Product;
• Leadership experience or strong potential and readiness to step into a technical leadership role.

• Experience with AdTech or Programmatic Advertising (auction mechanics, high-scale decisioning);
• Experience with Google Cloud Platform (GCP), Kubernetes, and cloud-native environments;
• Familiarity with data-intensive applications, analytics platforms, and large-scale aggregations;
• Understanding of Machine Learning concepts and production ML integrations;
• Experience leading technical initiatives, mentoring engineers, or working with distributed external teams.

• →Design, develop, and maintain high-performance backend services in Go;
• →Analyze and optimize distributed systems and microservice-based architectures;
• →Drive engineering quality through code reviews, technical leadership, and best practices;
• →Contribute to architecture decisions, technology selection, and platform strategy;
• →Collaborate closely with Product Managers to translate business needs into scalable technical solutions;
• →Work alongside Data Engineering and Machine Learning teams to integrate data-driven capabilities into bidder workflows;
• →Help establish a strong engineering culture built around ownership, accountability, and continuous improvement.