Top Engineering Jobs

Lead Atlassian’s ITSM Analytics engineering organization, shaping a multi-pod team responsible for reporting, analytics, data pipelines, GraphQL APIs, React interfaces, and data infrastructure. Set technical direction, scale analytics products, drive performance and data quality, deliver enterprise-ready releases, and hire, coach, and retain senior engineers.

Build and improve backend applications and distributed systems, leading complex projects from technical design through launch. Responsibilities include solving architecture challenges, establishing standards, reviewing code, documenting systems, fixing high-risk bugs, collaborating across engineering teams, mentoring junior engineers, and transitioning expertise to Java development while considering scalability, performance, robustness, and customer impact.

Lead architecture and delivery of a secure, low-latency Kubernetes-based compute platform for AI agents and untrusted workloads. Own isolation, scheduling, lifecycle, networking, policy, observability, and control-plane capabilities across GCP and AWS. Drive cross-team outcomes from design to adoption, improve developer experience via APIs and automation, and champion reliability, security, performance, and cost efficiency while mentoring engineers and setting technical direction.

Lead the technical evolution and long-term architecture of Jira Data Management. Drive enterprise-scale data movement, governance, resiliency, reliability, performance, security, and observability initiatives. Own a 12–24 month platform roadmap, lead major architectural programs from strategy through delivery, conduct design and incident reviews, solve high-risk technical problems, and mentor senior and principal engineers across Jira Platform.

Lead a distributed engineering organization building developer infrastructure, AI measurement and evaluation frameworks, context retrieval pipelines, agentic workflow infrastructure, and developer tooling. Manage engineering managers and senior engineers, shape technical roadmaps, optimize reliability and costs, partner with product and executive leadership, and foster a high-trust engineering culture.

Senior Software Engineer role at Atlassian with flexible work-location options. The detailed job responsibilities and qualifications were not provided. Compensation ranges from $149,400 to $235,000 in U.S. geographic pay zones, with potential benefits, bonuses, commissions, and equity.

Lead engineering teams building and operating Atlassian’s Plato Data Platform across streaming ingestion and MPP query/serving. Own reliability, performance, cost, scale, data quality, and observability for high-scale production infrastructure. Manage hiring, coaching, retention, and development of senior engineers and managers while providing technical leadership in distributed systems, Kubernetes, and cloud data infrastructure on GCP or AWS.

Lead and grow a multi-pod engineering team building Atlassian’s JSM analytics platform. Own technical direction and delivery for custom metrics, insights, operations and assets reporting, spanning React frontends, GraphQL APIs, distributed data pipelines and cloud infrastructure. Drive products from early access through general availability while improving scale, performance, data quality and observability. Hire, coach and retain senior engineers and deliver analytics capabilities for enterprise customers.

Provides technical leadership on complex software projects from design through launch, addressing architecture, reliability, security, testing, and observability at scale. Leads company-wide engineering initiatives, establishes technical standards, mentors engineers, and promotes engineering excellence. Requires extensive full-stack development experience, strong communication, systems engineering expertise, customer-focused decision-making, and familiarity with A/B testing.

Leads technical strategy, architecture, and engineering execution across Atlassian’s Rovo Chat, Search, Growth, Apps, and Clients experiences. The role drives scalable AI foundations, Search and Chat convergence, personalization, experimentation, reliability, security, and operational excellence. It involves leading cross-organizational initiatives, partnering with product, design, data science, and machine learning teams, mentoring senior engineers, and shaping multi-year technical roadmaps for customer-facing applications.