Salary: $180,000 – $240,000

Remote: Hybrid

At TL Consulting, we simplify modern complexity with advanced, sustainable engineering. As a proudly Australian-owned consultancy with over 15 years of experience, we empower businesses to innovate and achieve measurable outcomes through scalable, cloud-native solutions. Our 50+ consultants operate across key sectors including banking, financial services & insurance (BFSI), government, retail, education and entertainment. This cross-industry expertise allows us to deliver customer-centric solutions that combine deep technical capability with a clear understanding of each client's strategic vision. Our approach leverages proven, scalable blueprints tailored to your business direction - enabling accelerated outcomes, maximised ROI, and sustainable long-term adoption.We maintain strategic partnerships with organisations that share our vision for a cloud-native future. Through our collaborations with Microsoft, GitHub and Databricks, we ensure our capabilities stay aligned with evolving best practices. These partnerships also provide access to innovation programmes, co-funding opportunities and dedicated support - helping us accelerate time-to-value for our clients.About the role The AI Engineer builds and operates AI-powered applications and agentic systems for TL's clients, with a focus on Azure AI Foundry, retrieval-augmented generation, and AI-assisted engineering practice. This is a hands‑on delivery role. You build what the solution design calls for and prove it works: deploying and integrating models, building retrieval and agent components, modernising existing applications and writing the evaluations that demonstrate output is fit to put in front of users. The ideal candidate is a capable software engineer with production AI experience who moves between client environments and technology stacks, and who is as interested in whether a solution works as in building it.KEY RESPONSIBILITIES AI Application & Agentic Engineering Deploy and configure models on Azure AI Foundry and equivalent platforms, and build the Terraform and CI/CD that provisions them.Integrate models into applications: inference clients, retry and timeout behaviour, structured output, streaming, and token and cost instrumentation.Build retrieval‑augmented generation pipelines covering chunking, embeddings, vector and hybrid search, and re‑ranking, and diagnose retrieval failures.Build agentic workflows across application runtime, GitHub Actions and Copilot Studio,



including recognising when a deterministic workflow is the better answer.Implement Model Context Protocol (MCP) servers and tool integration patterns where applicable.Application Modernisation & AI‑assisted Delivery Modernise existing applications full-stack, using AI‑assisted methods to accelerate delivery rather than only adding AI features.Work specification‑first: write and review the specification before implementation, and use it to drive coding agents.Apply GitHub Copilot, Claude Code and similar tooling within an agreed engineering workflow.Evaluation & Quality Build evaluation harnesses: golden datasets, regression suites, automated output comparison, and LLM‑as‑judge where appropriate.Run shadow evaluations comparing a new model or platform against an incumbent, and report what the data shows.Tune guardrails and content filters against real workload content and measure the residual false‑positive rate.Cost, Governance & Handover Instrument token usage, latency and cost, and attribute spend so it traces to a team or product.Work within the engagement's model and prompt governance: versioning, approval, and evaluation thresholds that gate a release.Document solutions so the client's team can operate them after handover, and contribute to internal knowledge sharing.SKILLS & EXPERIENCE Education Bachelor's degree in Computer Science, Software Engineering, Information Technology, Engineering, Mathematics or a related quantitative discipline.Equivalent demonstrable experience will be considered in place of a formal qualification. We assess on what you have built and shipped.Relevant certification is welcome but not required, for example Microsoft Azure AI Engineer Associate or Azure Developer Associate.Experience 2 to 4 years in software or platform engineering, including at least one AI or ML system taken to production and supported afterwards.Practical retrieval‑augmented generation experience, including the failure modes.Experience evaluating model output with a method more rigorous than reviewing a sample of responses.Exposure to client‑facing or cross‑team delivery.Technical Skills AI & LLM Engineering Hands‑on with Azure AI Foundry,



and able to reason about AWS Bedrock, Vertex AI and self‑hosted alternativesPrompt engineering, structured output and evaluation techniquesRetrieval‑augmented generation and agentic workflowsAwareness of open‑weight model serving and fine‑tuning approaches such as LoRAAzure & Cloud Azure AI Foundry and Azure AI servicesAwareness of Azure Data Factory, Logic Apps and API ManagementCloud‑native application patternsEngineering & DevOps Strong programming capability in Python; full‑stack capability across one of C#, TypeScript or equivalentTerraform and CI/CD with GitHub Actions or Azure DevOpsGitHub Copilot and AI‑assisted development practiceSpec‑driven developmentCost & Governance Awareness of model costing and usage‑based billingUnderstanding of content filtering, guardrails and responsible AI basicsSoft Skills Excellent verbal and written communication. Much of the value produced on an engagement is a document someone else acts on.Ability to explain complex technical concepts to non‑technical stakeholders.A team player who can work effectively with diverse delivery teams to ensure a positive client experience.Ability to manage multiple priorities and work independently in a agile environment.Willingness to learn continuously. The tooling in this field turns over roughly every six months and we expect people to form a view by building, not by reading.Commitment to sharing knowledge: writing up learnings, running internal sessions, and transferring capability to client teams.WHY JOIN US Be part of a consultancy that values innovation, growth and professional development.Work with diverse, top‑tier clients across multiple industries, delivering impactful solutions.Dedicated time and budget for certification, conferences and deep work on new technology.Direct engagement with Microsoft and other partners, including co‑sell and reference architecture work.A clear engineering ladder with levels defined by scope and judgement rather than tenure.Competitive salary and benefits package.This is a Sydney based, permanent opportunity and will be hybrid in nature. No agencies please. Candidates must have valid visa with full work rights in Australia. Visas will not be transferred or sponsored.TL Consulting Group understands the importance of fostering a diverse and inclusive workplace. We are committed to ensuring that everyone, no matter their gender, identity, sexual orientation, race, ethnicity, religion, disability or age, has equal#J-18808-Ljbffr

📌 AI Engineer (Haymarket)
🏢 TL Consulting Group
📍 Haymarket