Create the unified platform where users discover, evaluate, access, and manage available services, tools, and applications from a single interface – web-based, CLIs, or even MCPs
Perform lifecycle for our different CI/CD tools (running on different platforms such as Microsoft Azure, Kubernetes or Virtual Machines on premise) to ensure security, availability, and maintainability of the platforms
You will work on complex systems involving servo motion, gantry systems, multi-axis synchronization, robotics integration, and industrial PC-based control systems.
Leading engineer role for all global contact center applications; including - cloud providers, internal/external infrastructure, telephone providers, interaction recording, workforce management, reporting, session border controllers, and integrated equipment, devices, and infrastructure.
Manage day-to-day operation activities, analyse statistics and write status and progress reports, and present findings to stakeholders and higher management.
Own assigned deliverables throughout the software development lifecycle, including design, implementation, integration, troubleshooting, and deployment.
Innovation & R&D: Evaluate emerging technologies, frameworks, and methodologies, conducting proof-of-concepts (PoCs) to strategically introduce them into our programme.
Define, monitor, and report on SRE metrics such as Service Level Indicators, Service Level Objectives, availability, latency, error rates, throughput, and error budgets
We are looking for an experienced backend engineer to join our Global Payments Engineering team. In this role, you will design and build scalable payment infrastructure that powers cross-border payment solutions across multiple markets. Working closely with regional Product, Business, and Compliance teams, you will deliver localized payment capabilities, integrate with global payment partners, and help drive our international business expansion.
Embed security assumptions at the architecture level, designing and implementing defense-in-depth for critical modules to reduce single points of failure and ambiguous trust boundaries.
Work closely with Product Managers, Business Development, data teams, and regional stakeholders to translate growth objectives into practical engineering solutions.
Analyse Gen AI outputs for quality, accuracy, and alignment with requirements; identify common failure modes (hallucination, bias, irrelevant answers, factual errors).