Staff Data Engineer - AI Data Platform

About the role

Checkbox, a Series A AI-native SaaS company for in-house legal teams, is looking for a Staff Data Engineer / Data Architect to own its data strategy and architecture. The role reports directly to the VP of Engineering, partners with one other Staff Data Engineer and stays hands-on in designing and delivering the systems. It sits within the Data team that serves the product engineering streams building AI agents.

Key responsibilities

• Own the data and AI reference architecture: base data sources, intelligence services, context and retrieval layers, API and MCP surfaces, and secure, tenant-isolated access patterns.
• Design patterns that let product teams build AI features on shared foundations, and set architectural principles for storage, retrieval, serving, tenancy, observability and compliance.
• Architect context and retrieval layers for AI agents and GenAI products, and model customer, matter, workflow, document, event and operational data.
• Evaluate and select data patterns such as transactional stores, operational data stores, warehouses, vector stores, semantic layers, knowledge graphs and event streams, and make buy-vs-build decisions.
• Own architecture across integrations, eventing, operational data, transactional data and AI-ready data, including data contracts, event models and ingestion patterns.
• Build shared data capabilities for analytics, AI agents, workflow automation and customer-facing products, and improve data quality, lineage and observability.
• Treat security, tenancy and compliance as first-order concerns, with auditable, tenant-isolated access and least privilege.
• Set technical direction, mentor engineers, share the load with the other Staff Engineer on the Greenfield Data Platform, and act as the senior technical voice for data architecture.

Required profile

• Significant experience as a senior data engineer, principal data engineer, data architect, staff engineer or similar technical leadership role.
• Proven experience building data and context foundations for AI products in production.
• Experience designing data architectures across transactional, operational, analytical and AI-ready systems.
• Experience with multi-tenant SaaS systems and strong buy-vs-build judgement.
• Comfortable leading technical direction while still building, reviewing and shipping, and mentoring engineers.

Required skills

• Modern data platform patterns: data contracts, event-driven architecture, ingestion, transformation, observability, lineage and governance.
• AI data patterns: retrieval systems, embeddings, semantic modelling, vector search, knowledge graphs, context engineering or agentic workflows.
• Bonus: AWS infrastructure, event-driven systems (queues, Pub/Sub, streaming), and experience with AI agents, MCP surfaces or legal tech.

What we offer

• Competitive salary and hybrid working with team days in the Sydney CBD office.
• Direct reporting line to the VP of Engineering and high ownership of a tier-one engineering function.
• Personal learning and development budget, flexible leave policy and expense policy.