Albert Attard
Principal Java Success Consultant @Oracle
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WORK HISTORY
Principal Java Success Consultant @Oracle
North Rhine-Westphalia, DE
Partner with enterprise customers to design and implement production-grade systems, combining hands-on engineering with architectural guidance across cloud-native Java platforms.Work directly with customer engineering teams to identify and deliver AI-powered use cases that extend existing systems, focusing on measurable business impact.Design and build AI-driven features using OpenAI-compatible approaches and libraries such as Spring AI and LangChain4J, including retrieval-augmented generation (RAG), structured outputs, and controlled system interactions.Rapidly prototype and iterate on AI solutions with customers, moving from proof-of-concept to production-ready implementations while addressing constraints such as latency, cost, reliability, and governance.Enable engineering teams to use AI tools such as Codex and similar technologies effectively in their daily development workflows, improving productivity, accelerating prototyping, and supporting code generation, exploration, and problem solving.Run hands-on sessions and workshops to demonstrate how AI can be applied to real-world development tasks, helping teams build confidence and practical capability beyond initial experimentation.Develop reference implementations and prototypes that demonstrate how LLM-based capabilities can be integrated into enterprise Java systems.Work side-by-side with customer teams through workshops and hands-on sessions, acting as a technical advisor to accelerate delivery and adoption.Support internal teams in adopting AI practices by sharing patterns, best practices, and practical guidance for integrating AI into existing engineering workflows.
EDUCATION
Royal Holloway, University of London
Master’s Degree, MSc Information Security
ABOUT ALBERT ATTARD
Staff Java Engineer specialising in building and integrating production-grade AI systems in enterprise environments.I work directly with customers to design and deliver AI-powered solutions, both by integrating LLM capabilities into existing systems and by enabling teams to build new applications using AI tools such as Codex and similar developer-focused technologies.With over 20 years of experience in distributed systems, low-latency platforms, and complex integrations, I bring a strong foundation in performance, reliability, and system design. More recently, I have been working hands-on with customers to rapidly prototype and implement AI solutions using technologies such as Spring AI and LangChain4J, focusing on structured outputs, retrieval-based approaches, and safe system interaction.I follow an experiment-driven, iterative approach, working side-by-side with engineers to move from early prototypes to production-ready systems while addressing real-world constraints such as latency, cost, accuracy, and maintainability.In addition to delivery, I enable teams to adopt AI effectively by teaching practical ways to use AI tools in real development workflows, improving productivity, code quality, and speed of delivery.
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