Lead the design and delivery of knowledge graph and machine learning systems that infer personal work context from connected tools. Build graph inference pipelines, schemas, permission-aware APIs, Rovo Chat integrations, and MCP-compatible CLI experiences. Establish evaluation frameworks, improve retrieval and grounding, provide technical direction across teams, mentor engineers, and ensure responsible, privacy-safe AI systems operate reliably at production scale.
Engineering | Seattle, United States | Remote, Remote | Mountain View, United States or Remote | San Francisco, United States
Working at Atlassian
Atlassians can choose where they work - whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity.
At Atlassian, we're on a mission to unleash the potential of every team. Central to that mission is the Teamwork Graph (TWG) - Atlassian's real-time, permissions-aware knowledge graph that unifies people, teams, projects, content, and activities across Atlassian and connected third-party tools. We believe the next frontier of AI-powered teamwork is personal working environment context: knowing who you collaborate with, what you're actively working on, and which documents matter right now - so that Rovo Chat, agents, and the TWG CLI can deliver answers that are precise, relevant, and actionable.
We're seeking a Principal Machine Learning Engineer (P60) to lead and design knowledge graph projects that build this personal working environment context layer and serve it at scale through Rovo Chat and the Teamwork Graph CLI.
What You'll Do
Build Personal Work Context Graphs
Improve Rovo Chat with Graph Context
Deliver Context Through Graph APIs & CLI
Lead Across Teams
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.
Please visit
Working at Atlassian
Atlassians can choose where they work - whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity.
At Atlassian, we're on a mission to unleash the potential of every team. Central to that mission is the Teamwork Graph (TWG) - Atlassian's real-time, permissions-aware knowledge graph that unifies people, teams, projects, content, and activities across Atlassian and connected third-party tools. We believe the next frontier of AI-powered teamwork is personal working environment context: knowing who you collaborate with, what you're actively working on, and which documents matter right now - so that Rovo Chat, agents, and the TWG CLI can deliver answers that are precise, relevant, and actionable.
We're seeking a Principal Machine Learning Engineer (P60) to lead and design knowledge graph projects that build this personal working environment context layer and serve it at scale through Rovo Chat and the Teamwork Graph CLI.
What You'll Do
Build Personal Work Context Graphs
- Design graph inference pipelines that surface collaborators, active work, documents, and projects from connected tools.
- Define schemas, permissions, and evaluation frameworks for reliable inferred context.
Improve Rovo Chat with Graph Context
- Integrate personal context into Rovo Chat to improve relevance, groundedness, and efficiency.
- Build and measure context-selection strategies with the Rovo Chat team.
Deliver Context Through Graph APIs & CLI
- Build low-latency, permission-safe APIs and CLI experiences for personal work context.
- Enable MCP-compatible agents to query a user's work environment in real time.
Lead Across Teams
- Provide technical leadership across Knowledge AI, Teamwork Graph, and product teams.
- Mentor engineers and champion responsible, privacy-safe AI and data quality.
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.
Please visit
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