As a Data Acquisition Engineer (AI Systems), you will work at the intersection of software engineering, browser automation, distributed systems, and AI. You will help design and build platforms that collect, process, and deliver structured data from a wide range of public sources while continuously improving their reliability and resilience.
Support in building and improving an evaluation algorithm that learns from past human decisions to assess the quality of new AI suggestions and identify when human review is required.
Design and implement a Unified Knowledge Layer for AI agents, including context management, indexing, retrieval, governance and distribution strategies.
Develop and execute the organisation's learning and development strategy, aligning capability-building initiatives with business objectives and future workforce needs.
Departmental Leadership & Performance: Direct and manage the Technical Training Department across multiple brand portfolios, ensuring high operational efficiency, measurable training KPIs, and continuous competency growth.
Design, build, and maintain MLOps pipelines for training, testing, deploying, and monitoring AI/ML models in production, ensuring stable, reliable, and scalable performance.
Responsible for designing, building, and operating scalable data ingestion, transformation, and serving capabilities across a modern hybrid cloud data platform, ensuring solutions are reliable, secure, reusable, and aligned to enterprise architecture and governance standards.