The Senior AI Engineer (Agents & Automation) designs, builds, evaluates, and operates the AI agents, tools, and pipelines that put AI to work across the business, with digital platforms as the primary focus, and the whole enterprise as the canvas.

This is a hands-on engineering role at the heart of our AI Centre of Excellence. You will ship production-grade AI agents and, just as importantly, build the enterprise-grade rollout machinery around them: a scalable, evaluated, versioned, and governed way of releasing agents, prompts, tools, MCP connectors, RAG, and data pipelines. You care as much about how reliably and repeatably we ship and operate AI as about the agents themselves

.

You will operate in an agent-led delivery model where AI agents are trusted to do meaningful work under human supervision with the emphasis on outcomes, quality controls, and repeatability rather than approving every step. You'll reengineer the process before you automate it, document what you build, and feed reusable patterns and guardrails back into our enterprise AI standard s.In this newly created role, you will help move the organisation from promising pilots to a governed, compounding portfolio of agents that genuinely add value—no fluff, no hype, no rewor k.

Get Excited

ToBuild Agents That Mat

- ter

Design and ship production AI agents across the taxonomy: conversational/user-facing, knowledge & Q&A;, workflow/process automation, decision-support, and monitor

- ing.Reengineer and optimise the underlying business process first (mapping it in BPMN), then automate it—because automating a broken process just makes waste fas
- ter.Integrate tools and MCP connectors with least-privilege, allow-listed access, and clean separation between agents that read and agents that
- act.Build retrieval-augmented generation (RAG), vector, and data pipelines grounded in governed data, so agents answer from a single source of tr
- uth.Contribute to creating agents that generate dashboards, answer business questions,



and release insights from enterprise data and the governed semantic layer on Databricks, with evaluation, cost monitoring, and release controls built into the delivery proc
- ess.Note: Data science and machine learning experience is a strong plus, particularly where it supports forecasting, segmentation, recommendation, decision-support, or user intelligence use ca

ses.

Make the Rollout Enterprise-

- Grade

Build the evaluation harness: quality, groundedness, safety, bias, and prompt-injection testing, combining LLM-as-judge with human review, so agents earn their re

- lease.Establish versioning and CI/CD for everything—agents, prompts, tools, MCPs, and pipelines with environments, release gates, rollback, and kill-swi
- tches.Stand up observability and AgentOps: telemetry, monitoring, cost tracking, drift detection, and continuous improvement loops in produ
- ction.Define repeatable, supervised delivery patterns and progressively embed them into day-to-day engineering and operational pra

ctice.

Engineer for Trust, Cost, an

- d Scale

Build with security, privacy, and governance by design—human-in-the-loop by default for anything touching end-users, financials, or systems of record; full logging and trace

- ability.Manage performance, reliability, and cost in production; reduce recurring issues through standard p
- atterns.Document thoroughly—runbooks, agent cards, decision records—so what you build is supportable and r

eusable.

Raise the Whole Organisati

- on's Game

Partner with and coach business AI champions; where a high-value area is stuck,



embed temporarily to deliver the first agent and han

- d it back.Contribute SME insight, reusable patterns, and delivery learnings into our enterprise AI standards and guardrails through established architecture and governan

ce forums.

The Skills & Experience Y

- ou Offer Us

3 years

’ experience in a fast-paced, large-scale commercial or enterprise
- environment.Proven experience designing, building, and shipping LLM/agent applications to production (not just
- prototypes).Strong software engineering fundamentals in Python and/or TypeScript (or similar), with solid API and version-contr
- ol practice.Hands-on with agent frameworks and orchestration, tool/function calling, and the Model Context Pro
- tocol (MCP).RAG, embeddings, and vector databases, plus strong SQL and data pipeline skills; comfortable working with structured and unstru
- ctured data.Evaluation and LLMOps / AgentOps: building eval harnesses, versioning prompts and agents, CI/CD, observability, and guardrails for AI syste
- ms at scale.Prompt and context engineering, with an eval-driven, iterati
- ve approach.Strong analytical and problem-sol
- ving skills.Results-driven with excellent organisation and prioritisatio
- n abilities.Calm, adaptable, and effective in fast-paced e
- nvironments.Proactive mindset with strong initiative and acc
- ountability.Commercially astute with sound busines
- s judgement.Cooperative communicator, able to engage technical and non-technical s

takeholders.

Ou r Core Values

Whether we’re innovating behind the scenes, collaborating across global teams, or serving our clients, these principles guide eve

- rything we do:

U

ser-Centricity: We keep the end-user in min
- d at all times.Mutual Respect: We foster an inclusive environmen
- t for everyone.Simplicity: We strip away unnecess
- ary complexity.Accountability: We own our work an
- d our outcomes.Agile Execution: We move with purpos

e and velocity.

📌 Artificial Intelligence Engineer (Melbourne)
🏢 Sirius.
📍 Melbourne