Staff Data Engineer
- Compensation
- Not disclosed
- Location
- Sydney
- Work setup
- Hybrid
- Seniority
- Staff
- Employment
- Full time
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Nice to have
- Experience working on AI agents, agentic workflows, GenAI platforms or AI-native SaaS products
- Experience designing MCP or API surfaces for data and context access
- Experience with legal tech, workflow automation, enterprise SaaS or document-heavy products
- Experience with AWS-based data and platform infrastructure
- Experience with event-driven systems, queues, Pub/Sub patterns or streaming architectures
- Experience with data security, compliance, auditability and enterprise customer requirements
- Experience growing a small data function from early foundations into a scalable team
Full description
Staff Data Engineer
Full-time | Hybrid | SydneyReports to: VP of EngineeringAbout Us:
Checkbox is a Series A technology company building AI-native SaaS for in-house legal teams. Our platform helps legal teams manage how work is raised, understood, routed, actioned and resolved across the business.
We are now transforming our SaaS ecosystem into agentic-first products, using AI agents and intelligent workflow automation to change how legal work gets done. To support this, we are investing deeply in the data, context and retrieval foundations that power reliable AI product experiences.
This is a critical next chapter for Checkbox. Our data platform needs to become more than infrastructure. It needs to become a competitive moat.
The Role
We are looking for a Staff Data Engineer / Data Architect to own Checkbox’s data strategy and the architecture that delivers it.
This role reporting directly to the VP of Engineering. You will join our tier-one Data team, being deeply hands-on in the design and delivery of the systems you define.
The Data team exists to serve the product engineering streams building AI agents, so close day-to-day partnership with Product, Engineering, AI and Platform teams is central to the role.
You will own the data and AI reference architecture that underpins our agentic product direction. This includes base data sources, intelligence services, context and retrieval layers, API and MCP surfaces, and the secure data access patterns required to give AI agents compliant, tenant-isolated context.
This is not a role for someone who only wants to design from a distance. We need someone who has built data and context foundations for AI products in production, can make pragmatic architecture decisions, and can lead by building.
What You’ll OwnData and AI Reference Architecture
- Own the data and AI reference architecture across Checkbox’s product ecosystem
- Define how base data sources, intelligence services, APIs, MCP surfaces, context engines and retrieval layers fit together
- Design patterns that allow product engineering streams to build AI features on shared foundations rather than reinventing data access each time
- Establish clear architectural principles for storage, retrieval, serving, tenancy, observability and compliance
- Work hand in glove with the Principal Engineer on architecture that spans application, platform, eventing, data and AI systems
Context, Retrieval and AI Data Foundations
- Architect and build the context and retrieval layers that power AI agents and GenAI product experiences