AI Circle - JR Academy

🚀【Sydney】AI Engineering: Agents, Harness & Production

Wed, Sep 23 · 5:30 PM AEST

Nutanix Sydney Office, Nutanix Sydney OfficeLevel 10, Maritime Trade Towers201 Kent Street, Sydney NSW 2000, Sydney, AU

What does it take to turn an AI demo into reliable software—and keep it working in production?
​Join Sydney’s AI and engineering community for an evening of practical talks, technical demonstrations, and conversations with industry practitioners. We’ll explore how AI systems move from early prototypes to real business applications, with a focus on engineering reliability, data integrity, and accountable decision-making.
​🔴 You may also hear about job openings and potential referral opportunities from our speakers. Meet engineers from leading tech companies, learn about their work, and make connections that could support your next career move.

## ​🎤 Featured Talks

​1️⃣ From Demo to Prod: Building Reliable Software with AI
​2️⃣ Governing AI in Investment: From Data Integrity to Decision Accountability

## ​💻 Event Format

• ​90 minutes: Welcome, speaker presentations, and technical demonstrations
• ​30 minutes: Live Q&A and technical networking
• ​Language: All sessions will be delivered in English
• ​Food and drinks provided

## ​✨ Event Highlights

​🎯 Start with Real Business Problems
​Explore how to identify practical AI use cases from real user and business needs, then translate them into clear, testable product and engineering goals.
​🛠️ Focus on Production Engineering
​Understand the challenges involved in moving from a prototype to a live application, including system architecture, data pipelines, model integration, evaluation, business workflows, and reliability.
​📈 Build for Long-Term Operation and Scale
​Launching an AI application is only the beginning. Learn how ongoing monitoring, cost management, performance optimisation, and iteration help systems support more users and evolving business needs.
​🤝 Connect with Sydney’s Tech Community
​Meet engineers, developers, product leaders, and AI practitioners from the local community. Exchange project experiences, discuss technical challenges, and explore opportunities to collaborate.

## ​🎙️ Meet the Speakers

​Mark
​Senior Data & AI Engineer @ Rainmakr.AI & Savana ETFs
​Mark focuses on AI and data-driven applications in financial technology, designing and optimising data pipelines, cloud infrastructure, and AI-powered investment systems. He drives internal research and innovation, integrating large language models, agentic AI, and advanced analytics into investment research and operational workflows to improve automation and support better investment decisions.
​Junyi Men
​Founder & Engineer @ Proairesis
​Junyi combines a founder’s product perspective with an engineer’s technical approach to bring ideas to life. Her work connects product discovery with software development, bridging user needs and technical implementation to build useful products and applications.
​Jignesh (Jiggy) Kakkad
​Principal AI Engineer / Software Engineering Lead @ Quantium
​Jiggy brings experience across software engineering, artificial intelligence, and cybersecurity, with a focus on robust, scalable enterprise systems and cross-team technical leadership. His current work centres on large language models and retrieval-augmented generation (RAG), using Azure and the OpenAI API to integrate AI capabilities into enterprise platforms.
​Blaise Paradeza
​Senior AI Software Engineer @ Quantium
​Blaise focuses on production AI applications and full-stack systems. His current work includes conversational AI systems built with LangGraph and the Model Context Protocol (MCP). He also works across frontend and backend development, Kubernetes deployments, LiteLLM, Langfuse, cloud infrastructure, and CI/CD, bringing hands-on experience in deploying and operating AI systems in production.

## ​🔍 What You’ll Learn

​Through the talks and discussions, we’ll explore:

• ​How to identify valuable, practical AI use cases
• ​How to turn loosely defined AI ideas into clear product and engineering goals
• ​What it takes to move from prototypes and proofs of concept to production
• ​How to build AI systems that are reliable, maintainable, and robust
• ​How to integrate AI into existing products, platforms, and enterprise workflows
• ​How to establish evaluation, quality control, and feedback mechanisms
• ​How to balance accuracy, response time, operating costs, and user experience
• ​How to address performance, reliability, and scalability challenges
• ​How to improve AI applications through monitoring, feedback, and continuous iteration

## ​👥 Who Should Attend?

​This event is for:

• ​AI and machine learning engineers
• ​Software engineers and solutions architects
• ​Data engineers and data scientists
• ​Technical leads and engineering managers
• ​AI product managers and digital transformation leaders
• ​Founders exploring practical AI applications
• ​Technology professionals interested in AI engineering and production systems

​Whether you’re already building AI applications or exploring a move into AI engineering, join us for practical perspectives and conversations with people working in the field.

## ​💬 More Than a Technical Talk

​This meetup is also a space for open, practical conversations within Sydney’s AI and engineering community.
​Bring a project you’re building, an engineering challenge you’re working through, or a question about applying AI. Connect with others facing similar challenges and explore how AI can be applied across different products, teams, and industries.

## ​📌 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
🍽️ Refreshments: Food and drinks provided

## ​🎟️ Register Now

​Join us for an evening of AI engineering insights, practical discussion, and connections with Sydney’s tech community.
​Register to secure your place.

JR Talks Vol. 9: What Do AI Application Engineers Do in China?

Wed, Sep 23 · 9:00 PM AEST

·

Online

Online

Please note: This event will be conducted in Mandarin Chinese.

## 🎟️ Register Here

https://jiangren.com.au/events/6a842e7427fe430dd9386941

# What Does an AI Application Development Engineer Actually Do in China?

A practical breakdown of real Chinese job descriptions—from responsibilities and technology stacks to projects and interviews. 🔍
“AI Application Development Engineer,” also known as an LLM Application Engineer or Large Model Application Engineer, is becoming an increasingly popular career direction for developers in China.
However, job requirements vary widely. Some positions focus on integrating LLM APIs, while others require experience with RAG, AI Agents, MCP, private deployment, model evaluation, data security and cost optimisation.
After reading dozens of job descriptions, many developers still have the same questions:

• 💼 What does this role involve day to day?
• 🔄 How is it different from a backend engineer or algorithm engineer?
• 🧠 What technical skills and project experience do companies really value?
• 🛠️ What should experienced IT professionals learn before making the transition?
• 📄 What kind of AI project can strengthen a resume and withstand interview questions?

In this livestream, we will examine representative AI application development job descriptions from the Chinese market across four key areas: responsibilities, technology stacks, project experience and interview expectations.
No vague industry predictions and no confusion between algorithm research and application development. We’ll focus on real roles and practical projects: what problems companies expect you to solve, what capabilities they need, and how your existing experience can transfer into AI application development.

## 🔍 What We’ll Discuss

1｜What does an AI Application Development Engineer actually do?
Follow the complete workflow of an AI feature—from business requirements and model integration to knowledge-base development and production deployment.
2｜What are real job descriptions asking for?
Break down responsibilities, technology stacks, experience requirements and project expectations to identify what different companies have in common.
3｜Why is calling an LLM API not enough?
Understand the gap between a quick demo and a production-ready AI application, including evaluation, logging, security, reliability and cost control.
4｜What should you learn first: RAG, Agents, MCP, evaluation or deployment?
Build a structured AI application development roadmap instead of learning isolated buzzwords.
5｜How can people from different IT backgrounds make the transition?
Explore transferable skills and capability gaps for backend, frontend, full-stack, testing, data and DevOps professionals.
6｜What projects can strengthen your resume and survive interview deep dives?
Learn how interviewers assess business context, technical decisions, system design, evaluation results and production deployment.

## 🎙️ Guest Speakers

Max
NLP Algorithm Researcher｜CETC Cyber Security
Max holds a Master’s degree in Computer Science from Trinity College Dublin and a Bachelor’s degree from Sun Yat-sen University.
With seven years of NLP research and engineering experience, he has led multiple commercial LLM applications involving RAG, AI Agents and Prompt Engineering, with extensive experience taking AI projects from zero to production. He is also the first author of four Chinese national patents and several core journal papers.
Ding
Architect｜Tencent
Ding is a Computer Science graduate from the Australian National University and currently works as an architect at Tencent.
He has received offers from six leading companies, including Tencent, Alibaba, ByteDance, Meituan, Dewu and AWS, giving him extensive experience in technical interviews, career preparation and DevOps learning.
Junjie Yan
Founder｜Chengdu Fengzhilan Technology
Junjie is an AI technology specialist and the founder of Chengdu Fengzhilan Technology.
He focuses on OPC, artificial intelligence and enterprise technology solutions, providing AI consulting and project delivery services with practical experience in AI research and real-world implementation.
Gang Wang
Senior Data R&D Expert｜China Mobile Internet
Gang specialises in data engineering and enterprise data applications.
He has extensive experience in large-scale data development, system architecture and business implementation, with a strong understanding of how data and AI technologies can be applied in real enterprise environments.

## 👥 Who Should Attend?

• Backend, frontend and full-stack developers considering a transition into AI application development
• Testers, data professionals and DevOps engineers who want to participate in AI projects
• Developers who have learned RAG or AI Agents but are unsure how close they are to a real role
• People who have built AI demos and want to turn them into stronger portfolio projects
• Computer Science students planning a career in AI
• IT professionals who want to enter the AI industry without starting from algorithm research

## 🗓️ Event Details

📅 Date: Wednesday, 23 September 2026
🇨🇳 Beijing Time: 7:00 PM–9:00 PM
🇦🇺 Sydney Time: 9:00 PM–11:00 PM
💻 Format: Online livestream
🗣️ Language: Mandarin Chinese
🎟️ Admission: Free · Registration required

## 🌟 About JR Talks

JR Talks is a technology and career conversation series presented by JR Academy, exploring the future of AI, education and technology careers.
We believe that true craftspeople are not defined by the times they live in. They keep learning, continue practising and ultimately create meaningful change. ✨

AI Engineer Open Class: From LLM Applications to AI Agents | Melbourne

Thu, Sep 24 · 5:30 PM AEST

ANNG Gallery, Level 17/60 Albert Rd, South Melbourne VIC 3205, Australia, South Melbourne, AU

What does it take to build an AI agent?
Connecting an LLM, writing prompts and building a chat interface are only the beginning. When your application needs to work with knowledge bases, external tools and business processes, a new set of engineering challenges emerges.
Join JR Academy in Melbourne for a free, in-person open class exploring how AI agents work and what it takes to build a reliable, production-grade agentic system.
We’ll also introduce our updated AI Engineer Cohort 07 programme, including its curriculum, project structure and learning requirements.
🎤 Meet your speaker — Roy
Roy is an experienced AI Engineer who has worked on agentic AI and software development projects at Deloitte and V2.ai. His work includes AI systems for supply chain risk management, invoice automation and faster software development.
In this session, Roy will explain the inner workings of AI agents and how to build reliable, production-grade agentic systems.
🚀 What we’ll cover
1. From LLM applications to agent systems
Understand the relationship between model calls, AI workflows and agents, and explore how to choose the right approach for different tasks.
2. RAG and citations: answers grounded in evidence
Explore retrieval-augmented generation (RAG), source citations and no-answer mechanisms, including how systems should respond when the available information is insufficient.
3. MCP tools and tool calling
Learn how agents connect to external tools, and why tool definitions, parameter validation, permissions and result handling matter.
4. Execution boundaries and human approval
Discuss stopping conditions, confirmation for important actions and failure handling to make agent behaviour more controlled and predictable.
5. Evaluation and execution tracing
Discover how to assess output quality, track execution, diagnose errors and improve your system through ongoing evaluation.
🛠️ Introducing AI Engineer Cohort 07
Our updated programme follows one Agent project over 13 weeks, progressively developing it through five stages:

• System Foundation: Define requirements, architecture, data and business workflows.
• First AI Workflow: Connect AI to a practical process and produce structured outputs that can be checked and reviewed.
• Grounded Intelligence: Add RAG, citations, no-answer behaviour and quality evaluation.
• Agent System: Integrate MCP tools, execution boundaries, human approval and secure memory.
• Production Standard: Introduce execution controls, model routing, evaluations, red teaming and rollback mechanisms.

The final project brings together code, architecture, evaluations, execution logs and release evidence.
The programme includes 12 Theory Live sessions and 13 Practice Live sessions, combining explanations of core concepts with live coding to develop the same project from Week 1 to Week 13.
At the open class, we’ll walk through the learning schedule, project expectations and prerequisites to help you assess whether the programme fits your goals.
👥 Who should attend?

• Software, backend and full-stack developers looking to expand into AI engineering.
• Data and ML engineers interested in building complete AI applications.
• DevOps and cloud engineers curious about agent operations and deployment.
• IT students with programming experience exploring AI project development.
• Developers who have built a RAG or agent demo and want to strengthen their testing, evaluation and engineering skills.
• Professionals preparing for AI engineering roles or interviews.

💬 Bring your questions and meet the community
There will be time for Q&A and networking. Bring your project ideas, technical questions or learning plans:

• Where should I start with my current technical background?
• I’ve built a small AI project—what should I learn next?
• How can I turn individual skills into a complete, working system?
• How can I explain my AI project’s design, trade-offs and results in an interview?
• Is AI Engineer Cohort 07 a good fit for my goals?

Connect with fellow developers and AI learners, exchange experiences and explore your next step in AI engineering.
📍 When and where
Thursday, 24 September 2026
5:30 PM–7:00 PM · Melbourne time
ANNG Gallery
Level 17, 60 Albert Road, South Melbourne VIC 3205
🎟️ Free admission — reserve your spot and join us in Melbourne!

​🤝 Host and Venue
Host: JR Academy
Venue: ANNG Gallery
Venue Support: CloudTech Group