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 Role
This 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 workflows
create deterministic evaluation harnesses and regression suites that make agent quality measurable
implement OpenTelemetry tracing to improve the observability of agent runs
model regulatory reasoning through Bayesian networks and related probabilistic techniques




develop expert-facing interfaces that allow legal specialists to inspect and edit regulatory rules
deploy and operate secure, observable and supportable platforms on AWS
work directly with partners and subject‐matter experts to translate legal judgement into robust technical systems
contribute to appropriate governance and assurance for AI used in regulated work.
About You
We 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 stage
a rigorous evaluation discipline and the ability to demonstrate whether a model or system change has improved performance
experience applying Bayesian inference, Bayesian networks or comparable statistical reasoning to a real-world domain
strong Python software‐engineering capability
sufficient React and TypeScript experience to build usable, expert‐facing interfaces
production AWS experience, including security and identity considerations relevant to regulated data
sound judgement when working with non‐technical experts
a strong understanding of governance requirements associated with AI in regulated environments.
Exposure to AI assurance standards such as ISO ***** will be viewed favourably
We 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.

📌 Lead Ai Engineer, Agentic Systems (New South Wales)
🏢 MinterEllison
📍 New South Wales