Top Azure Jobs in Sydney

Design, build, and maintain frontend products, platform services, infrastructure, microservices, libraries, tools, and applications powering Atlassian Cloud. Develop scalable, low-latency systems using modern web architectures and distributed systems principles. Implement, integrate, tune, test, and troubleshoot software while collaborating with designers and engineers in an agile environment to improve user experiences.

Lead and resolve billing, usage metering, and cloud cost escalations by diagnosing metering discrepancies, usage spikes, billing anomalies, and quota enforcement. Collaborate with Product, Engineering, and Finance to escalate bugs and improve visibility; create tooling, playbooks, and training to enable global teams; communicate cost impact to stakeholders and surface customer feedback to influence product roadmap.

Build scalable backend and frontend services for MongoDB’s application modernization platform. Develop APIs, data pipelines, code analysis tools, dependency graphs, and schema recommendation features. Collaborate with product, engineering, and design teams; contribute to architecture, testing, CI/CD, code reviews, troubleshooting, and technical documentation. Senior engineers will mentor teammates, lead complex feature design, and support recruiting and interviewing.

Build and improve core AI and machine learning infrastructure enabling teams to develop, train, evaluate, deploy, and operate ML models and pipelines. Design scalable distributed systems, support end-to-end ML lifecycles, implement MLOps automation, collaborate with product engineering teams, lead projects from design through launch, review code, document solutions, and mentor junior engineers. Work may include dataset curation, LLM fine-tuning, model serving, monitoring, and generative AI systems.

Lead complex backend engineering initiatives from technical design through launch. Design architectures, deliver solutions used across teams and products, resolve high-risk issues, establish code review and documentation standards, and influence company-wide technical decisions. Mentor engineers, evaluate performance and reliability trade-offs, and contribute to developer experience and productivity using modern cloud platforms, multiple programming languages, and CI/CD practices.

Supports sales opportunities from qualification through close by gathering customer networking requirements, contributing to technical solution design, adapting solutions, advising on products, preparing proposals and presentations, and maintaining customer and partner relationships. The role is intended for recent computer science, software engineering, or network engineering graduates with knowledge of networking, cloud computing, AI, machine learning, data analytics, sustainability, and data center infrastructure.

Supports technical sales opportunities from qualification through close by understanding customer networking needs, developing solution designs, advising on products, preparing proposals and presentations, communicating with customers and partners, and coordinating technical resources. Requires a recent computer science or engineering graduate with networking, cloud, AI, analytics, and data center knowledge, strong communication skills, analytical ability, and an interest in technology sales.

Provides technical support for technology partners and mutual customers using MongoDB and related systems. Responsibilities include troubleshooting application, database, storage, networking, and cloud issues; guiding solution integrations; coordinating multi-vendor escalations; onboarding partners; documenting architectures and known issues; and reducing interoperability risks. The role also develops partner knowledge bases, communicates best practices, supports releases, and becomes a technical specialist capable of handling advanced diagnostics and escalations independently.

Leads pre-sales AI solution architecture for enterprise customers, addressing business and technical challenges with ServiceNow AI products. Responsibilities include customer engagement, demonstrations, proof-of-concepts, value-based selling, sales support, technical presentations, marketing events, product training, and solution development. The role requires expertise in generative AI, deep learning, LLMs, cloud AI platforms, data stores, and AI-driven automation, with travel up to 50% of the time.

Develop, deploy, and improve distributed big-data pipelines for data ingestion, fusion, machine learning, and network analysis. Lead end-to-end data engineering solutions, improve scalability and reliability, support security and compliance reviews, and serve as a technical expert in customer engagements. Collaborate with engineering, data science, product, and public-sector stakeholders while evaluating tools and mentoring teams.

Leads and grows an AI Deployment Engineering team responsible for delivering agentic AI implementations, customer adoption, and measurable business outcomes. Owns portfolio roadmaps, staffing, delivery standards, technical quality, customer relationships, and cross-functional coordination. Establishes reliable, safe, auditable deployment practices and remains technically hands-on with agent architecture, evaluations, integrations, and production troubleshooting.

Designs and deploys agentic AI workflows and integrations for enterprise customers. Leads implementations from scoping through adoption, builds APIs and automations, configures data connections and guardrails, evaluates agent performance, and manages human-in-the-loop processes. Acts as the primary technical customer contact while coordinating engineering, data science, product, and customer success teams. Owns implementation roadmaps, requirements, acceptance criteria, documentation, and measurable delivery outcomes.

Owns strategic enterprise accounts in Australia’s financial services sector, developing executive relationships, creating expansion opportunities, and driving complex SaaS sales cycles. Responsibilities include account planning, pipeline generation, forecasting, territory strategy, executive engagement, and positioning Dynatrace across observability, cloud modernization, security, AI, automation, and digital experience initiatives. The role requires collaboration with technical, customer success, professional services, marketing, partner, and executive teams.

Designs enterprise file and object storage architectures for AI, analytics, data lake, and enterprise workloads. Partners with customers on solution sizing, data flows, performance, scalability, and protection requirements; leads technical workshops, benchmarks, and proofs of concept; and presents recommendations to technical and executive audiences. The role supports presales engagements, RFIs/RFPs, competitive positioning, and product roadmap feedback while requiring expertise in S3, NFS, SMB, AI/RAG pipelines, and modern storage platforms.

Leads and scales Snowflake’s global Frontier Engineering organization, defining technical strategy for forward-deployed engineering teams. Builds customer-facing engineering engagements, partners with executives, oversees production software delivery, hires and develops engineering leaders, and connects customer needs to product direction. The role requires extensive software engineering leadership, experience managing managers across countries and time zones, and familiarity with cloud data platforms, AI/ML, and modern application development.

Lead design and delivery of scalable, reliable backend services for Azure infrastructure. Own distributed-system design, implementation, testing, and operations. Drive incident response, on-call rotations, observability, automation, code reviews, and mentor engineers to improve reliability and operational excellence.

Supports customer discovery, secure cloud endpoint solution design, technical demonstrations, presentations, proof-of-concept activities, and technical decision-making. Collaborates with sales, engineering, customer success, and partners to advance opportunities and deliver strong customer experiences. Builds expertise in Windows 365, Azure Virtual Desktop, Intune, Entra ID, Defender, and endpoint management through training, coaching, certifications, and customer engagements.

Leads Snowflake’s ANZ AI/ML consulting team, coaching technical architects and overseeing partner delivery. Provides billable technical leadership, guides generative AI and agent projects from design through production, reviews architecture and quality, manages customer relationships and escalations, coordinates capacity, and partners with Product and Engineering. The role emphasizes production LLM practices, governance, evaluation, observability, cloud architecture, and customer outcomes, with up to 25% onsite travel.

Leads technical pre-sales for enterprise data management solutions, including discovery, solution design, product demonstrations, proof-of-concept engagements, executive briefings, RFP responses, and partner enablement. Translates customer requirements involving cloud infrastructure, data security, governance, privacy, and compliance into measurable business outcomes. Collaborates with sales, product, engineering, marketing, customer success, and channel partners throughout complex enterprise sales cycles.

Provides L2/L3 application support for complex web-based and integrated production systems. Investigates incidents and service requests using SQL, logs, APIs, databases, and monitoring tools; manages issues through resolution within SLAs; communicates with clients; performs health checks; coordinates technical escalations; maintains documentation; supports users; and identifies automation and process improvements.

Build and evolve payer-facing experiences supporting online invoicing, payment processing, and money movement workflows. Collaborate with developers, product managers, and UX designers to deliver secure, reliable customer experiences. Contribute to DevOps improvements, Agile delivery, technical vision, knowledge sharing, and high-quality software development using modern programming languages, cloud platforms, containers, and CI/CD tools.

Lead DevOps Engineer responsible for the reliability, scalability, security, and performance of critical technology platforms. The role provides infrastructure and operational support, builds monitoring and deployment tools, manages configurations and repositories, advances continuous delivery, and automates manual processes. It requires hands-on expertise in Azure, Kubernetes, CI/CD, scripting, databases, microservices, Kafka, and Terraform, along with technical leadership and a focus on operational excellence.

Own network reliability and performance across 350+ sites. Design, deploy, operate, and optimize enterprise networking, SD-WAN, wireless, routing, switching, firewalls, VPNs, segmentation, and secure access. Monitor threats, support disaster recovery planning, and automate network operations using Python, Ansible, and APIs. Collaborate with technology teams, managed service providers, and vendors while maintaining governance and delivering infrastructure upgrades.

Design, automate, and maintain enterprise Azure and GCP infrastructure. Develop Terraform modules, landing zones, deployment pipelines, and secure cloud networking. Modernize legacy systems, apply FinOps and Zero Trust practices, resolve critical production incidents, and implement backup, recovery, monitoring, and disaster recovery solutions in collaboration with architecture, cybersecurity, network, and digital teams.

Build, manage, and optimize AWS cloud infrastructure supporting a secure, scalable fintech platform. Responsibilities include infrastructure automation, DevOps, security and compliance, reliability engineering, monitoring with Splunk, troubleshooting, and managing Docker and Kubernetes environments. The role partners with development teams, improves system performance and resilience, controls infrastructure costs, and drives continuous platform improvement.