AI Engineer Fullstack in Melbourne

Engaged through PAAR Systems, supporting a Big Four Australian bank.

PAAR Systems is an Australian technology company building and running enterprise automation and AI platforms for banking and other regulated industries. We work at the intersection of software engineering, applied AI and regulatory obligation — where an AI solution is not just a demo, it is something a bank has to run reliably in production and be able to explain to its regulator.

We are resourcing an AI Engineer to join a major data & AI transformation programme for one of Australia’s Big Four banks. The programme is building production AI capability across the bank — from data foundations through to deployed, AI-powered applications — and this role sits at the centre of it: someone who can take an AI or machine learning idea from prototype to a robust, full-stack production system used by real teams and customers.

Key skill: strong full-stack software engineering ability in Python is essential — building and shipping production services, APIs and applications, not just notebooks — combined with hands-on applied machine learning and experience building AI solutions end to end.

WHAT YOU'LL DO

• Design, build and ship full-stack AI-powered applications and services — backend APIs, data and model integration layers, and where needed front-end interfaces — that put AI capability directly in front of business and customer-facing teams.
• Build and productionise machine learning and AI models, including GenAI/LLM-based solutions, taking them from prototype through to reliable, monitored production services.
• Own the engineering quality of AI solutions: API design, testing, CI/CD, observability, performance and security, to the production standard expected in a regulated bank.
• Integrate AI solutions with the bank’s core data platform (Snowflake) and enterprise systems, working closely with data engineering and data science.
• Partner with product owners, risk and compliance stakeholders to ensure AI solutions meet model risk, explainability and governance requirements.
• Contribute to reusable AI engineering patterns, internal libraries and platform capability — for example RAG pipelines, agent frameworks and evaluation harnesses — that raise delivery speed and quality across the programme.
• Mentor other engineers on production ML/AI engineering practice and full-stack delivery.

WHAT YOU'LL BRING

• 4+ years’ full-stack software engineering experience, with strong Python skills across both backend services and application logic.
• Hands-on experience applying machine learning and building AI solutions end to end — from data preparation and model development through to deployment as production services.
• Practical experience with modern AI/GenAI tooling — LLM APIs, retrieval-augmented generation, prompt/context engineering, or agentic frameworks.
• Solid engineering fundamentals: API design (REST/GraphQL), databases and SQL, automated testing, CI/CD, cloud deployment.
• Experience working with a modern data platform (Snowflake preferred) to source and serve data for AI/ML workloads.
• Comfortable operating in a regulated environment, with an appreciation for model risk, security and responsible AI practice.
• Strong communication skills — able to work directly with data scientists, product owners and risk stakeholders.

NICE TO HAVE

• Front-end development experience (React, TypeScript or similar) for building internal AI tooling or customer-facing interfaces.
• Experience with MLOps/LLMOps tooling (MLflow, LangChain/LangGraph, vector databases, Airflow, CI/CD for ML).
• Cloud platform certification (AWS, Azure or GCP).
• Exposure to APRA prudential standards (CPS 230, CPS 234) or AI governance frameworks.
• Experience with Snowflake Cortex, Snowpark or similar.

ENGAGEMENT DETAILS

• Location: Melbourne, VIC (onshore) — hybrid, with regular time on the bank’s site.
• Engagement type: Permanent or contract — tell us your preference.
• Work rights: Applicants must hold full working rights in Australia.

WHAT WE OFFER

• Direct involvement in a flagship data & AI transformation for one of Australia’s largest banks.
• A small, senior delivery team with short decision paths and genuine technical ownership.
• Flexible hybrid working arrangements, and your choice of permanent or contract engagement.
• Compensation that is competitive and commensurate with experience — we are happy to discuss it early so neither of us wastes time.