Technical Product Operations Manager

We are a leading trading platform with top-rated products that have won prestigious industry awards for cutting-edge technology and seamless client experience. The company is ambitiously expanding globally and has a talented, ever-growing engineering team.

• Degree in STEM or another quantitative field.
• Minimum 4 years' experience in technical programme management, engineering operations, or delivery management in a high-performance software engineering environment.
• Proven success delivering cross-team technical programmes within multi-team organisations.
• Strong technical understanding of modern software systems including services, deployments, queues, metrics, Kubernetes, Kafka, CI/CD, releases, and rollbacks.
• Ability to read architecture diagrams, tech design documents, and ADRs to assess readiness for review.
• Proficiency in SQL and confidence working with dashboards, APIs, and Jira.
• Practical experience using AI tools to improve individual and team productivity.
• Strong stakeholder management and facilitation skills with ability to drive decisions amidst unclear ownership.
• Clear and concise written communication suitable for senior audiences.
• Proactive ownership mentality focused on accountability and execution.

• Run cross-team technical programs such as platform migrations, dependency removals, standardisation initiatives, decommissioning, and large infrastructure changes, breaking broad goals into plans with named owners.
• Facilitate technical discussions and secure decisions with committed delivery dates, especially where ownership is unclear.
• Maintain accurate status views of each programme's phase, blockers, owners, and delivery dates.
• Produce concise, accurate status reporting for engineering leadership.
• Drive and improve company-wide engineering processes, including sharpening existing ones and establishing new ones.
• Gather engineer feedback to identify and remove unnecessary friction, translating findings into concrete process changes.
• Instrument processes to measure key metrics such as review turnaround time and rework rate.
• Query data directly using SQL, dashboards, and APIs; reconcile data across various systems such as Jira.
• Identify recurring manual engineering tasks and automate them using AI where beneficial, measuring actual savings.
• Build lasting assets like playbooks, templates, runbooks, automated reporting, and agent workflows, and assist colleagues in adopting effective AI practices.