Staff Software Engineer – Experimentation & Decisioning Platform

Overview

As a Staff Software Engineer in the Payments Performance pillar, you will steer long-term technical direction for high-scale experimentation and optimization systems. You’ll align multiple engineering teams to architectural priorities, unblock obstacles, and balance technical excellence with pragmatic impact. You’ll coach engineers, shape cross-functional solutions with Data Science and ML teams, and drive continuous improvement for reliable, low-latency backend systems. This is a chance to influence global payments infrastructure at scale and contribute to a fast-growing fintech platform.

Pay / Benefits

• hybrid working model
• three days per week in the office
• opportunity for growth and impact
• recognition for delivering results
• collaborative culture and strong team support
• focus on owning meaningful challenges

Responsibilities

• Define and drive long-term technical direction for the Experimentation and Optimisation platform to scale impact
• Collaborate with Data Science, Platform and ML Engineering teams to shape what is built
• Mentor engineering teams and solve complex distributed systems challenges in Go
• Elevate engineering standards and foster a culture of continuous improvement
• Translate requirements into clear engineering roadmaps and architecture decisions
• Promote engineering excellence through code, architecture, and operational best practices

Key requirements

• Extensive hands-on experience building, operating and scaling cloud-based distributed systems (AWS)
• Excellent Go (Golang) programming skills with understanding of concurrent, memory-efficient, low-latency architectures
• Proven track record implementing and scaling experimentation systems or similar data-intensive backends
• Strong coaching and mentorship abilities to raise engineering standards
• Clear communication and collaboration skills across multidisciplinary teams
• Data-driven, detail-oriented approach to infrastructure with low latency
• Accountability to internal customers and engineering colleagues

• coaching and mentorship
• clear communication
• collaboration across teams
• Go (Golang)
• AWS
• distributed systems

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