Top Azure Jobs in Melbourne

This role leads enterprise-scale AI and Data transformation programs, acting as a trusted advisor to senior executives, and shaping data strategies and governance frameworks.

Design and build core infrastructure, ensure reliability of multi-cloud Kubernetes clusters, automate operations, and build machine learning infrastructure.

Provide L2/L3 IT support, manage Azure services, corporate network devices, Active Directory, and cloud infrastructure, ensuring reliable IT Security systems while collaborating in a global team.

The Compliance Engineer will manage compliance certifications, assist sales with security queries, conduct risk assessments, and enhance compliance tooling across APAC regions.

The role involves ensuring the reliability of cloud infrastructure, incident management, system design, and collaboration with engineering teams for ClickHouse Cloud.

Lead design and delivery of scalable AI and data solutions, set engineering standards and guardrails, experiment with emerging AI tools, collaborate with product stakeholders, mentor engineers, and improve platform performance, reliability and cost across cloud-based pipelines.

Generate pipeline across APAC by researching and prospecting target accounts, executing personalized outbound campaigns (email/phone/LinkedIn), engaging technical buyers, partnering with AEs on territory plans, maintaining CRM hygiene, experimenting with messaging and AI tools, and consistently meeting pipeline-generation goals.

As a Senior AI Engineer, you will develop and implement AI capabilities to enhance business processes and customer experiences, collaborating with teams to deliver scalable solutions.

The Principal Customer Solutions Engineer designs, implements, and leads mainframe modernization projects, providing technical solutions and customer support while managing project risks and team dynamics.

Lead design, develop, test, and support of highly scalable, reliable Azure Storage services. Provide technical leadership, improve observability and AIOps, ensure security and compliance, and support high-availability services used by millions with on-call responsibilities.

Design, implement and optimise Azure cloud infrastructure and IaC using Terraform. Support production environments, improve automation and CI/CD/GitOps practices, troubleshoot cloud issues, and collaborate with stakeholders and vendors to uplift cloud platforms and engineering standards.

Drive Azure and AI solution sales for nonprofit and humanitarian customers in ANZ. Qualify and close deals, build pipeline, lead technical/value conversations, envision and run workshops/POCs, and guide customers from experimentation to production with governance and responsible AI practices.

Lead end-to-end delivery of AI-first, full-stack products for enterprise clients: lead discovery, architect and build AI-powered systems, scope and manage delivery to production, embed with client teams, and champion AI-native practices and prompt/context engineering.

Lead client-facing delivery of AI-first, full‑stack products from discovery through production. Embed with client teams to design, build and deploy LLM-powered systems, apply prompt/context engineering, validate AI-generated code, and drive adoption. Own technical outcomes, identify risks, and communicate with stakeholders across product, architecture, code, and infrastructure.

Embed with strategic customers to prototype, build, and productionize full-stack AI and agentic applications. Advise on AI strategy, codify repeatable solution patterns, mentor teams, and feed product improvements.

Lead design, development, and operational support of the API platform (Apigee/Azure APIM). Provide platform subject-matter expertise, onboard/migrate APIs, improve security, scalability, monitoring, CI/CD, infrastructure-as-code, and developer experience.

Lead design, build, and deploy production-grade Generative AI solutions. Architect and optimise RAG pipelines and vector DBs, integrate AI via secure APIs/microservices, manage prompt lifecycle, implement MLOps/versioning/monitoring, and mentor engineering teams.

Lead design and delivery of enterprise-scale generative AI and multi-agent systems. Define reference architectures, RAG and vector knowledge layers, integration fabrics, observability, governance, and Responsible AI frameworks. Assess readiness, build roadmaps, coordinate cross-functional teams, and mentor engineering talent.

Lead pre-sales technical engagements to architect, demo, and deliver Protegrity data protection solutions across cloud, hybrid, and on-prem environments. Run POCs, map data flows, produce solution designs, collaborate with sales and services, mentor peers, and validate deployments using AWS/Azure/GCP and container platforms.

The Controls Engineer will implement battery energy storage systems, manage stakeholders and utilities, ensure high-quality deliverables, and develop new tools for continuous improvement.

Act as the primary technical authority for ANZ sales: design CNAPP solutions, lead POCs and demonstrations, integrate Upwind into customers' cloud and CI/CD environments, educate stakeholders on cloud security best practices, and enable partners and account teams with technical collateral and training.

The Sales Engineer will support channel partners, provide technical guidance, manage POC engagements, and articulate the value of Menlo Security products to various stakeholders while working closely with internal teams and partners.

Develop and maintain scalable backend services and APIs, collaborate with frontend developers, and lead new features and infrastructure improvements.

Investigate issues, define technical requirements and specifications, and work with developers to build, test and release enhancements to the WebRater application. Analyse integrations, data flows and platform performance, troubleshoot defects, and support delivery while upskilling other BAs on technical approaches.

Embed with strategic customers to design, build, and deliver production-grade AI/LLM solutions. Lead discovery, scoping, PoCs, integrations (APIs, data pipelines, RAG/vector DBs), production rollouts, and handoffs. Troubleshoot complex data/infra/model issues, collaborate with sales and product teams, and translate customer learnings into prioritized product improvements.