Jobs at Atlassian

Lead enterprise security architecture across endpoint, identity, network, cloud, and data. Define controls, review major initiatives, automate control deployment (IaC/PaC), mentor engineers, and drive zero-trust and cloud security strategy at scale.

Lead design and delivery of scalable ML/AI infrastructure and lifecycle tooling. Collaborate with product teams to enable dataset curation, model training, serving, monitoring, and deployment. Drive architecture, mentor engineers, contribute code reviews, and partner across teams to launch ML capabilities used across Atlassian products.

Lead technical strategy and multi-year roadmap for search and vector infrastructure powering Atlassian AI. Drive cross-team initiatives for semantic search, agentic retrieval, and RAG; ensure scalable, cost-effective ML serving with strong reliability and FinOps discipline; mentor senior engineers and raise organizational engineering craft.

Build and maintain core ML infrastructure and platforms enabling model development, training, deployment, monitoring, and MLOps. Partner with product teams to design scalable, fault-tolerant ML systems, fine-tune LLMs, curate datasets, and drive production launches while mentoring engineers.

Lead and grow an ML engineering team responsible for the end-to-end ML lifecycle: data collection, preprocessing, model development, deployment, evaluation and monitoring. Research and implement scalable ML and generative AI techniques (recommendation and agentic systems), mentor and hire engineers, drive pragmatic, business-focused solutions, and communicate technical results to stakeholders.

Lead and grow a high-performing ML team to design and deliver end-to-end AI features for DevAI products. Drive LLM integration, prompt engineering, technical strategy, project delivery, stakeholder alignment, and process optimization while mentoring engineers and managing performance.

Design, build, and operate scalable, low-latency search and retrieval systems powering Atlassian products. Develop and serve production ML models (neural rankers, embeddings, rerankers) using PyTorch and Triton. Implement vector indexing and RAG/agentic retrieval pipelines, ensure observability and cost optimization, manage on-call/runbooks, and collaborate cross-functionally while mentoring junior engineers.

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 design, build, and production deployment of AI/ML solutions for customers. Architect integrations and microservices, analyze complex data, manage AI risk and compliance (e.g., GDPR), mentor engineers, and align technical solutions with business objectives to drive measurable outcomes.

Lead product vision, strategy, and execution for Rovo Chat, Atlassian's AI-driven conversational interface. Prioritize adoption and quality, drive multi-turn conversation improvements, integrate knowledge across first- and third-party sources, partner cross-functionally to ship features, define success metrics, and champion responsible AI practices for safe, transparent conversational experiences.

Lead design, development, and production deployment of AI/ML solutions across Atlassian products. Code in Python/JavaScript, architect APIs and microservices, implement Rovo/LLM-based features, manage risk and compliance (GDPR), mentor engineers, and align technical solutions with customer and business objectives.