Cloud & Infrastructure Sydney schedule

During this 5-minute networking session, the aim of the game is to go and meet three people you don't already know. Use the questions on the screen to guide your conversation. Have fun!  

Learn how the most successful technology leaders are redefining their role, influence, and value proposition as AI becomes central to competitive strategy.

• From technology steward to business strategist: Transition from managing IT services to architecting competitive advantage through strategic AI infrastructure
• New leadership competencies: Develop skills in AI business cases, stakeholder alignment, and risk assessment beyond technical expertise
• Organisational influence and governance: Establish new reporting relationships, decision authority, and board-level communication positioning technology leaders as core business strategists

What we can learn from the Customer Experience with online shopping and apply it to the Developer Experience with cloud and infrastructure

• Demystify Developer Experience (DevEx), Internal Developer Platforms (IDPs), and Platform Engineering
• See the connection between DevEx, IDPs, Platform Engineering, and business outcomes
• Understand the value of scaling continuous delivery (CD) and its impact on DevEx

Speaker:

Mike Nguyen, SVP, Technical Success, Octopus Deploy

Architect foundations that support both current operations and future innovations without requiring wholesale replacement.

• AI-native architecture design
• Emerging technology talent strategies: Evolve organisational capabilities blending traditional expertise with AI operations and cloud-native architectures
• Adaptive governance for innovation: Balance innovation enablement with operational stability, enabling rapid technology evaluation and integration

Speaker:

William Cross, Head of Technology, ColCap Financial Group

Moderator:

Kate Romanova, former Group Head of Technology, Strategy and Innovation, ex-Qantas

Defining, implementing and scaling AI strategy that is integrated with your core objectives, creating a foundation for sustained competitive advantage.

• The icare context: our view and usage of AI
• Translating AI potential to tangible outcomes: Define a value-driven roadmap that aligns AI investments with strategic goals
• Governance and the human element of AI: Implement governance frameworks, change management, and talent models to navigate AI's complexity
• Building the AI-ready organisation: Create foundational infrastructure and capabilities to support organisation-wide AI adoption

Speaker:

Moderator:

The landscape is shifting again. A handful of organizations are moving beyond isolated pilots and starting to build genuinely differentiated capability using agentic workflows, multimodal AI, and real-world signals from systems of record, IoT, and digital twins. That acceleration creates a familiar trap: plenty of AI activity, but only a small portion compounds into durable advantage, while the rest quietly becomes expensive noise.

Some use cases behave like true alpha. In quant terms, alpha is not interesting tech, it’s repeatable outperformance versus a baseline, net of cost and risk. In AI transformation, the baseline is the current operating model (or the best available standard SaaS capability). A use case is true AI alpha when it delivers measurable uplift that competitors cannot easily replicate, and that uplift remains positive after implementation effort, operating cost, adoption friction, compliance overhead, and reliability risk.

What we’ll cover:

• How to spot true AI alpha in the gap between current operations and the future operating model
• How to distinguish alpha, beta, and loss-makers using a simple lens that supports clear decisions
• How to prioritise and sequence the right bets while keeping momentum and avoiding over-investment
• How to package a use case into a board-ready investment case
• How to make sure the chosen bets are realistic to run in production, not just exciting in a pilot

Speaker:

Leo Arkhipov, AI & Digital Transformation Practice Lead, 365mesh

Sponsored by Westcon & AWS

Build resilient platforms that balance developer agility with robust controls, leveraging AI-driven intelligence to predict failures and accelerate recovery.

• Preventative controls in cloud environments: Balance the risk of using preventative controls to protect availability without constraining cloud-native innovation and developer velocity

• Proactive availability strategies: Shift from reactive recovery to predictive failure detection and automated response using intelligent monitoring and orchestration

• Developer freedom versus platform governance: Navigate the balance between team autonomy and enforcing controls that ensure security and reliability

Speaker:

Jason Sandery, Head of Cloud Services, Commonwealth Bank

Moderator:

Kutlu Omeroglu, Chief Engineer - Public Cloud, Commonwealth Bank

It’s clear that our landscape is changing. We’re experiencing a disruption larger than we did in the dot-com era. Organisations are rapidly building and shipping more differentiated software than ever before accelerated by our new AI-driven agent capabilities. This velocity combined with the fact that the vast majority of modern software is built on Open Source, forces us to ask a critical question. How do we embed trust into the Open Source Software supply chain? In this session, we’ll explore: 

• How Open Source Software is built and distributed
• Evolving threats we face within the software supply chain
• How we must trust and verify to reduce the risk of the next SolarWinds, XZ utils & Shai Hulud

Speaker:

 Brett Drayton, Solutions Engineer, Chainguard  

Hear how organisations are designing strategic infrastructure to optimise AI capabilities across various deployment models.

• AI-first strategy: Design infrastructure and services optimised for AI workloads, ensuring scalability and flexibility
• Enterprise AI enablement: Create platforms and capabilities empowering business units to leverage AI effectively
• Digital infrastructure strategy: Align technology architecture with business goals, future-proofing infrastructure for market demands

Speakers:

Amit Kumar, Enterprise Architecture Manager, Wesfarmers Industrial and Safety - Blackwoods 

Raj Daroch, General Manager, IT, MSS Security 

IT operations is moving beyond reactive monitoring toward autonomous, self-healing systems. In this session, explore how Agentic AIOps is transforming full-stack observability; enabling AI to not only detect and correlate incidents, but investigate root cause, recommend remediation, and increasingly execute resolution actions.

Gain practical insight into how organisations can reduce noise, accelerate mean time to resolution (MTTR), and shift from alert fatigue to intelligent, outcome-driven operations. The session will outline the architectural and operational steps required to evolve from traditional monitoring to autonomous IT and what it takes to turn AI from a dashboard feature into a decision-making engine.

Speaker:

Paul Thomas, Senior Sales Engineer, LogicMonitor

• Citizen-centric metrics: Focusing on time savings and reduced friction

• Cloud efficiency gains: Scaling proven pilots with direct user impact
• Practical scaling: Tying investments to specific, measurable problems

 Speaker:

Transform infrastructure into a business value driver by aligning investments to growth and innovation outcomes.

• Strategic infrastructure financial governance: Implement predictive cost models and metrics to guide growth-focused investments
• Unified hybrid portfolio visibility: Gain cost transparency across cloud, private infrastructure, SaaS, and AI workloads
• Shared financial responsibility and accountability: Establish cost allocation and cross-functional accountability to drive smarter adoption

Speaker:

Arvind Shastry, FinOps Manager, Transport for NSW

Catherine Zhang, FinOps Lead, Australian Federal Agency

Moderator:

Jayden Le, Global Head of IT and Security, Zoomo  

True AI scalability is limited by the infrastructure it runs on. For most enterprises, that critical infrastructure is built on Java. This session reveals how to build a scalable, cost-controlled cloud foundation by optimising its most common workload. Learn how Azul helps enterprises with Java security and compliance, speeds up processing with less compute, and boosts Devops productivity and application development at scale. Leave with a blueprint to make your Java infrastructure a competitive advantage in the AI race.

Speaker:

Dean Vaughan, Vice President of Asia Pacific, Azul 

Cloud FinOps is often misunderstood as a purely cost-cutting/controlling exercise—but that’s far from the truth. In this session, we’ll debunk common myths and explore how FinOps can become a strategic enabler for innovation and growth. You’ll learn how to move beyond reactive cost management toward proactive financial governance that drives measurable business outcomes.

• Myth-busting: Why FinOps isn’t just about reducing spend—and how focusing solely on cost can limit scalability and innovation.
• Strategic alignment: Position FinOps as a value driver by linking cloud investments to organizational goals and growth strategies.
• Governance frameworks: Implement guardrails and accountability models that balance agility with financial discipline.
• Financial transparency: Achieve unified visibility across multi-cloud, SaaS, and AI workloads to eliminate waste and optimize ROI.
• Shared responsibility: Foster cross-functional collaboration between engineering, finance, and operations for sustainable success.

Drive adoption and business value by embedding change management across AI-enabled cloud transformation.

• Cross-functional alignment: Align business units, IT teams, and decision-makers around shared AI and cloud objectives.
• Strategic stakeholder engagement: Engage stakeholders early and continuously to champion AI-driven cloud capabilities.
• Bridging technology and strategy: Establish governance, communication, and metrics linking AI initiatives to measurable business impact

Speakers:

Tom Gao, Chief Technology and Digital Services Officer, City of Sydney

Aman Dayal, GM - Data, AI, Architecture, Coates

Moderator:

Kate Romanova, former Group Head of Technology, Strategy and Innovation, ex-Qantas

Evolve operating models, processes, and talent to accelerate digital business transformation.

• Reinventing talent and processes: Reinvent teams for rapid delivery, continuous improvement, and modern tech talent
• Redefining IT governance: Redefine governance to enable speed, empowerment, and agile experimentation
• Scaling innovation: Create a culture that rewards experimentation and scales new applications quickly

Speakers:

Stan Belikoff, Chief Technology Officer, C2O Group

Stevie-Ann Dovico,  Chief Technology Officer, Australian Financial Complaints Authority (AFCA) 

Moderator: 

Kritika Joon, Emerging Technologies & Innovation Leader

In the highly competitive age of digital transformation financial service organizations are facing accelerated urgency to improve their customer and employee experience while simultaneously reducing operating costs, and managing risk and compliance.

To meet these competing demands on their business, these organizations are racing to deploy deep learning to achieve a new competitive edge by optimizing their back office operations with intelligent document processing, personalizing their customer experience with cutting edge NLP models, and reducing fraud and risk using state-of-the-art deep learning.

AI is here and delivering new capabilities to help businesses solve large and complicated challenges. Join Bob Gaines to learn what that means for your business and how deep learning is helping organizations:

• Achieve higher compliance, faster and with lower costs • Dramatically improve Customer Experience • Reduce time to value from years to weeks

Sergio Rego is a customer engineer at SambaNova Systems where he helps clients deploy purpose-built, deep learning solutions in weeks rather than years. Sergio started his career in financial services, where he worked in strategy; active and index management; and product design and management. Sergio also served as a senior data scientist and team manager for a system integrator where he helped federal government agencies deploy ML and AI solutions.

In the highly competitive age of digital transformation financial service organizations are facing accelerated urgency to improve their customer and employee experience while simultaneously reducing operating costs, and managing risk and compliance.

To meet these competing demands on their business, these organizations are racing to deploy deep learning to achieve a new competitive edge by optimizing their back office operations with intelligent document processing, personalizing their customer experience with cutting edge NLP models, and reducing fraud and risk using state-of-the-art deep learning.

AI is here and delivering new capabilities to help businesses solve large and complicated challenges. Join Bob Gaines to learn what that means for your business and how deep learning is helping organizations:

• Achieve higher compliance, faster and with lower costs • Dramatically improve Customer Experience • Reduce time to value from years to weeks

Sergio Rego is a customer engineer at SambaNova Systems where he helps clients deploy purpose-built, deep learning solutions in weeks rather than years. Sergio started his career in financial services, where he worked in strategy; active and index management; and product design and management. Sergio also served as a senior data scientist and team manager for a system integrator where he helped federal government agencies deploy ML and AI solutions.