🚀AI Engineering in Practice: Real Challenges to Production Solutions
Details
Building an AI demo may take only a few days. Turning it into a reliable product that serves real users, integrates with existing business processes, and delivers lasting value is a completely different challenge.
When AI moves from experimentation to production, model performance is only the beginning. Teams must also address data quality, system integration, latency, operating costs, evaluation, reliability, security, and scalability.
On 23 September, JR Academy and KSUG will host an in-person AI Engineering event focused on how real-world AI projects move from business requirements and early prototypes to production deployment, monitoring, and continuous improvement.
This is not another high-level discussion about AI trends. It is a practical conversation about real use cases, engineering decisions, production challenges, and lessons learned from building AI systems in the field.
🎤 Guest Speakers
Mark
Senior Data & AI Engineer at Rainmakr.AI & Savana ETFs
Mark specialises in AI and data-driven fintech applications. His work covers data pipelines, cloud infrastructure, and AI-powered investment systems. He also explores how LLMs, agentic AI, and advanced analytics can improve investment research, automation, operational efficiency, and decision-making.
Jignesh “Jiggy” Kakkad
Principal AI Engineer / Software Engineering Lead at Quantium
Jiggy is an experienced technology leader with expertise across software engineering, artificial intelligence, and cybersecurity. He specialises in building robust and scalable enterprise systems and is currently exploring LLM and RAG applications using Azure and OpenAI APIs.
Blaise Paradeza
Senior AI Software Engineer at Quantium
Blaise focuses on production-ready AI applications and full-stack system development. His experience includes building AI-powered conversational systems with LangGraph and Model Context Protocol, as well as deploying frontend, backend, LiteLLM, and Langfuse services through Kubernetes, cloud infrastructure, and CI/CD pipelines.
💡 What You’ll Learn
- How to identify valuable business problems that are suitable for AI
- How to turn an AI idea into clear product and engineering objectives
- How to move from a prototype or proof of concept into production
- How to build reliable, scalable, and maintainable AI systems
- How to establish effective evaluation and quality-control processes
- How to balance accuracy, latency, operating costs, and user experience
- How to monitor and continuously improve AI applications
👥 Who Should Attend
- AI and Machine Learning Engineers
- Software Engineers and Solution Architects
- Data Engineers and Data Scientists
- Technical Leads and Engineering Managers
- AI Product Managers and Digital Transformation Leaders
- Founders and professionals building real-world AI applications
- Anyone interested in AI Engineering and production-ready AI systems
Whether you are already working on an AI project or want to better understand how production-grade AI systems are built, this event is an opportunity to learn from experienced practitioners and connect with Sydney’s local technology community.
Let’s move AI beyond the demo and into the real world. 🚀
📌 Event Details
📅 Date: Wednesday, 23 September 2026
⏰ Time: 5:30 PM–7:30 PM AEST
📍 Venue: Nutanix Sydney Office
🏢 Address: Level 10, Maritime Trade Towers, 201 Kent Street, Sydney NSW 2000
🌐 Language: English
🎟️ Format: Free in-person event