Information Technology Engineer

We are seeking an experienced Information Technology Engineer to design, develop, and manage enterprise-scale AI-driven data platforms supporting security operations, business intelligence, and operational analytics.

The successful candidate will play a key role in building AI-native solutions, developing scalable data architectures, implementing intelligent automation workflows, and delivering production-grade AI and data engineering platforms.

Responsibilities

• Design,develop, and maintain scalable AI-driven data platforms for security operations, analytics, and business intelligence.
• Build and deploy AI solutions including LLM-powered applications, AI agents, intelligent assistants, and workflow automation systems.
• Develop large-scale batch and real-time data pipelines using distributed processing technologies.
• Architect and optimise enterprise data platforms including data warehouses, data lakes, and streaming systems.
• Design and implement ETL/ELT pipelines, data models, and data quality frameworks.
• Develop knowledge graph platforms integrating operational data, metadata, lineage information, and business requirements.
• Build AI-powered automation solutions for monitoring, diagnostics, incident analysis, and operational improvement.
• Develop backend services, APIs, and AI application infrastructure using modern software engineering practices.
• Deploy and manage production systems using cloud platforms, Kubernetes, and distributed computing environments.
• Monitor, troubleshoot, and optimise system performance, reliability, scalability, and cost efficiency.
• Collaborate with security, operations, and business teams to deliver scalable technology solutions.
• Lead technical discussions, provide engineering guidance, and manage end-to-end delivery of complex AI and data projects.
• Evaluate emerging AI, cloud, and data engineering technologies for enterprise adoption.

Requirements

• Bachelor’s degree or higher in Computer Science, Software Engineering, Data Engineering, Artificial Intelligence, Information Technology, or a related discipline.
• Minimum 6 years of professional experience in data engineering, big data platforms, distributed systems, or AI engineering roles.
• Proven experience designing and deploying enterprise-scale data platforms.
• Strong hands-on experience in AI/LLM application development and integration.
• Experience with MCP (Model Context Protocol) server development and AI agent workflow implementation.
• Experience in LLM prompt engineering, tool integration, skill chaining, and AI workflow automation.
• Experience developing AI assistants, chatbots, and natural language query systems.
• Experience with knowledge graphs, graph-based search, and intelligent Q&A solutions.
• Strong understanding of AIOps concepts including automated monitoring, diagnostics, alerting, and remediation workflows.
• Strong experience with big data technologies such as Apache Spark, Apache Flink, Kafka, Hadoop, HDFS, MapReduce, and Presto/Trino.
• Experience designing and maintaining enterprise ETL/ELT pipelines and data warehouse solutions.
• Knowledge of data modelling concepts including ODS, DWD, DWS, and ADS layered architecture.
• Experience with technologies such as Hive, Apache Iceberg, Apache Paimon, HBase, MySQL, Elasticsearch, and BigQuery.
• Strong programming skills in Python, Scala, Java, SQL, and Shell scripting.
• Experience developing RESTful APIs and integrating enterprise applications.
• Experience with Google Cloud Platform technologies such as BigQuery, GCS, and Pub/Sub, or equivalent cloud platforms.
• Experience with Kubernetes, containerised applications, and production deployments.
• Experience with workflow orchestration tools such as Airflow.
• Knowledge of data validation, data quality monitoring, anomaly detection, and automated testing frameworks.
• Strong understanding of distributed system architecture, scalability, reliability, and performance optimisation.
• Strong analytical, troubleshooting, and problem-solving skills.
• Excellent communication skills with the ability to collaborate across engineering, security, operations, and business teams.
• Experience working in enterprise security, surveillance, defence, intelligence, or critical infrastructure environments.
• Knowledge of data security, access control, governance, and confidentiality practices.
• Ability to adapt quickly to evolving AI technologies and changing business requirements.