Technical Head of Enginering

Atlassian•San Francisco, CA

8d•$202,437 - $318,425•Hybrid

About The Position

We are hiring a Technical Head of Engineering to lead work on Atlassian’s Agent Platform. This role blends people-management responsibilities with deep technical leadership across applied ML, agentic systems, platform engineering, and production-quality AI experiences. The ideal candidate is a technically strong hands-on leader who is comfortable being either an individual contributor or a people manager. They can grow and lead a high-performing team while staying close enough to the technology to guide ML architecture, quality, evaluation, reliability, and platform decisions as well as write production code themselves. They should be comfortable operating at the intersection of product outcomes, developer experience, AI/ML systems, and scalable platform foundations. The Agent Platform team builds foundational capabilities that make AI agents useful, reliable, secure, and scalable across Atlassian. The team operates in a high-impact area connected to Rovo, Teamwork Graph, Jira agent workflows, and other Atlassian products. Its work helps Atlassian teams and customers create agentic experiences that can reason over work context, orchestrate across tools, and deliver meaningful outcomes in real product workflows. They also insure security of agentic products and help build evaluation systems. This is a strong fit for a leader who is excited by platform leverage: building reusable systems, patterns, and capabilities that help many product teams move faster while maintaining quality, trust, and operational excellence. Atlassian is investing heavily in AI-native and agentic experiences, and the platform layer is critical to making those experiences production-ready. The team needs a leader who can provide clear direction, build talent, and create an execution rhythm across ambiguous, fast-moving AI platform work. The role requires ML and systems depth to build alongside senior engineers and discuss architecture, evaluation, quality, reliability, and tradeoffs—not just people management. The leader will help translate broad AI strategy into practical platform capabilities that can be adopted across Atlassian products.

Requirements

Deep technical leadership across applied ML, agentic systems, platform engineering, and production-quality AI experiences.
Technically strong hands-on leader comfortable being either an individual contributor or a people manager.
Ability to grow and lead a high-performing team.
Ability to stay close enough to the technology to guide ML architecture, quality, evaluation, reliability, and platform decisions.
Ability to write production code.
Comfortable operating at the intersection of product outcomes, developer experience, AI/ML systems, and scalable platform foundations.
ML and systems depth to build alongside senior engineers and discuss architecture, evaluation, quality, reliability, and tradeoffs.
Ability to translate broad AI strategy into practical platform capabilities.

Responsibilities

Set technical and execution direction in partnership with product, engineering, ML, data, and platform stakeholders.
Lead, coach, and develop a team of engineers working on agent platform capabilities, including hiring, performance management, career development, and team health.
Be technically hands-on and write production code.
Guide technical decisions across applied ML systems, agent workflows, context retrieval, evaluation, quality measurement, observability, and production operations.
Create a strong operating cadence: goals, planning, prioritization, risk management, decision-making, and cross-team communication.
Ensure the team balances speed with quality, trust, security, privacy, cost efficiency, and operational readiness.
Partner with leaders across Rovo, Product and platform teams across Atlassian to align roadmaps and dependencies.
Build an inclusive, high-accountability team culture where engineers can do their best work and grow their craft.