Lead AI Engineer, Agentic Systems

MinterEllison; Sydney; On-site; AUD 120,000 - 180,000; Full time

Job summary

MinterEllison is seeking an experienced AI engineer to own end-to-end production AI systems in a regulated legal environment. You will lead orchestration across agents, evaluation, deployment, and governance interfaces to support expert oversight.

The role blends research-grade modelling with production platform engineering, offering direct collaboration with partners and subject-matter experts to translate legal judgement into robust, observable AI systems on AWS.

Qualifications

• Production experience with LLM agent frameworks and tool-calling architectures.
• Rigorous evaluation discipline for model changes.
• Experience with Bayesian inference or networks.
• Strong Python software engineering capability.
• Experience with React and TypeScript for expert interfaces.
• Production AWS experience, with security and identity for regulated data.
• Ability to work with non-technical experts.
• Understanding governance for AI in regulated environments.

Responsibilities

• design and build multi-agent orchestration, Model Context Protocol servers and 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.

Skills

LLM agent frameworks

Tool-calling architectures

Evaluation discipline

Bayesian inference

Python

React

TypeScript

Governance in AI

AWS security/identity

Tools

AWS

OpenTelemetry

Job description

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 opportunity 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 42001 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.