Lead Principal AI Engineer -- Teamwork Graph

Atlassian•San Francisco, CA

1d•$233,100 - $365,425•Hybrid

About The Position

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. Atlassian sits on one of the world’s largest corpuses of how work actually gets done—spanning Jira tickets, Confluence pages, Bitbucket commits, and Trello boards. The Teamwork Knowledge Graph AI team is responsible for connecting these dots to create a unified semantic understanding of work. We are looking for a Lead Principal AI Engineer to define the architecture and build the next generation of Agentic AI applications atop this massive Enterprise Knowledge Graph (EKG). This is a highly technical, hands-on leadership role (Individual Contributor track). You will operate at the intersection of research and product engineering, partnering directly with company leadership to define the AI application roadmap and shipping intelligence that powers the daily workflow of millions of users.

Requirements

Senior Technical Leadership: 15+ years of engineering experience with a significant focus on Applied AI/ML. You have experience driving technical strategy across multiple teams or the whole company.
Deep Agentic & LLM Experience: You have shipped complex LLM-backed applications to production. You understand the nuances of ReAct loops, tool calling, function schemas, and managing state in agentic workflows.
Knowledge Graph Fluency: You understand how to leverage graph structures (Nodes/Edges) to enhance retrieval. You know how to bridge structured data with unstructured semantic search.
System Architecture: You are an expert in distributed systems. You can design architectures that are scalable, secure, and cost-effective (token economics).
Product & Business Sense: You can bridge the gap between "what is possible with AI" and "what brings value to the customer." You are comfortable saying "no" to cool tech that doesn't solve a user need.

Responsibilities

Agentic features in all Atlassian products : Design and build autonomous agents capable of reasoning, planning, and tool execution over the Atlassian Knowledge Graph. You will define how agents consume context, utilize MCP (Model Context Protocol) tools, and interact with the Atlassian ecosystem.
Strategic Technical Leadership: Serve as the technical anchor for the organization. You will collaborate with VPs and Distinguished Engineers to shape the long-term AI architecture, moving us from simple chat interfaces to complex, multi-step agentic workflows.
Applied AI & LLM Ops: Lead decisions on model selection (proprietary vs. open source), context window management, and retrieval strategies (GraphRAG). You will drive the strategy for fine-tuning models on domain-specific Atlassian data when necessary.
Rigorous Evaluation: Move beyond "vibes-based" testing. You will architect robust evaluation frameworks (Evals) to measure agent performance, hallucination rates, and reasoning capabilities at scale.
Product Integration: You won't just build prototypes; you will integrate these capabilities directly into flagship products. You will use your strong product sense to ensure AI features solve real user problems, not just technical curiosities.