Our AI Enablement team builds agentic AI systems for use in legal work.
Its platforms support areas including large-scale due diligence, regulatory reasoning across FIRB, continuous disclosure, competition and environmental law, and visa eligibility assessment.
Several systems are already operating in production.
You will join a small, senior team working directly with partners and subject‐matter experts.
The team brings together AI engineering, probabilistic modelling, production platform delivery and practical legal expertise to create systems that experts can inspect and govern.Your RoleThis is an end-to-end engineering role for someone who wants to build production AI systems in a complex, regulated environment.
You will take ownership across agent orchestration, evaluation, deployment and the interfaces through which legal experts govern the systems they use.
The breadth of this role extends from research‐grade modelling to production platform engineering.
It offers the prospect to work with live systems, real users and the experts whose knowledge those systems are designed to encode.In this role, you will:design and build multi-agent orchestration, Model Context Protocol servers and supporting tooling for production legal workflowscreate deterministic evaluation harnesses and regression suites that make agent quality measurableimplement OpenTelemetry tracing to improve the observability of agent runsmodel regulatory reasoning through Bayesian networks and related probabilistic techniquesdevelop expert-facing interfaces that allow legal specialists to inspect and edit regulatory rulesdeploy and operate secure, observable and supportable platforms on AWSwork directly with partners and subject‐matter experts to translate legal judgement into robust technical systemscontribute to appropriate governance and assurance for AI used in regulated work.About YouWe welcome applications from experienced AI engineers who can demonstrate:production experience with LLM agent frameworks and tool‐calling architectures, including systems deployed beyond the prototype stagea rigorous evaluation discipline and the ability to demonstrate whether a model or system change has improved performanceexperience applying Bayesian inference, Bayesian networks or comparable statistical reasoning to a real-world domainstrong Python software‐engineering capabilitysufficient React and TypeScript experience to build usable, expert‐facing interfacesproduction AWS experience, including security and identity considerations relevant to regulated datasound judgement when working with non‐technical expertsa strong understanding of governance requirements associated with AI in regulated environments.Exposure to AI assurance standards such as ISO ***** will be viewed favourablyWe encourage applications from people of all ages, abilities, cultural backgrounds, genders (including trans or gender diverse), LGBTQ+ people and those with carer responsibilities.
We particularly encourage Aboriginal and Torres Strait Islander people to apply.
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📌 Lead Ai Engineer, Agentic Systems (Sydney)
🏢 MinterEllison
📍 Sydney