What you'll be doing

Drive the long-term technical direction and strategy for the Experimentation and Optimisation platform, ensuring solutions are built for impact and scale.
Collaborate cross-functionally with Data Science, Platform, and ML Engineering teams to shape both what is built and how.
Act as a coach and mentor to engineering teams, providing technical leadership to solve complex distributed systems challenges in Go.
Identify opportunities proactively and take initiative to elevate engineering standards, fostering a culture of continuous improvement.
Participate in collecting requirements and translate architecture/design initiatives into clear, actionable engineering roadmaps.
Serve as a role model for engineering excellence by championing best practices in code, architecture, and operational excellence.

Requirements

Technical leadership experience: setting direction, breaking down complex problems, and influencing across teams.
Extensive hands-on experience building, operating, and scaling complex, cloud-based distributed systems, primarily on AWS.
Excellent programming skills in Go (Golang), with strong knowledge of concurrent, memory-efficient, and low-latency backend architectures.
Proven track record in implementing, owning, and scaling experimentation systems, feature-flagging infrastructures, or similar data-intensive backend systems.
Ability to raise engineering standards through coaching, mentorship, and continuous platform improvement.
Strong presentation, communication, and collaboration skills to articulate technical and statistical concepts to multidisciplinary teams.
Detail-oriented and data-driven approach focusing on accuracy, thoroughness, and low latency.
Initiative and accountability towards internal customers and engineering colleagues.

Experience implementing adaptive experimentation ML solutions, such as contextual bandits, Bayesian optimization, or RL-based allocation.