AI Engineer_Fullstack

PAAR Systems; Sydney; Hybrid; AUD 140,000 - 190,000; Full time

Job summary

PAAR Systems is leading a data & AI transformation for a major Australian bank, building production AI capabilities from data foundations to deployed, AI-powered applications.

The role centers on turning AI ideas into robust, full-stack production systems with strong Python development, APIs, model integration and governance in a regulated context.

Qualifications

• 4+ years’ full-stack software engineering experience in production systems.
• Hands-on experience applying machine learning and building AI solutions end-to-end.
• Experience with modern AI/GenAI tooling (LLM APIs, retrieval‑augmented generation, prompt engineering).
• Solid API design fundamentals (REST/GraphQL), databases/SQL, automated testing, CI/CD, cloud deployment.
• Experience with Snowflake data platform or similar to source/serve AI data.
• Comfortable operating in a regulated environment with model risk and governance.
• Strong communication skills to work with data scientists, product owners and risk stakeholders.

Responsibilities

• Design, build and ship full-stack AI-powered applications and services.
• Productionise ML/AI models from prototype to reliable production services.
• Own the engineering quality of AI solutions (API design, testing, CI/CD, observability, security).
• Integrate AI solutions with the bank’s data platform and enterprise systems.
• Collaborate with product owners, risk and compliance on governance requirements.
• Contribute to reusable AI engineering patterns and internal libraries.
• Mentor other engineers on production ML/AI engineering and full-stack delivery.

Skills

Python

Full-stack engineering

GenAI/ML end-to-end

API design (REST/GraphQL)

Communication with stakeholders

Tools

Snowflake

MLOps / LLMOps tools

LangChain / LangGraph

Airflow

CI/CD tooling

Job description

ABOUT PAAR SYSTEMS

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.

ABOUT THE ROLE

We are resourcing an AI Engineer to join a major data & AI transformation programme for one of Australia’s Big Four banks. The programme isbuilding 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 realteams 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 simila PrA iAnR-p Slaystfteomrms P AtyI /LMtdL Rcoalpe aPbroifliiltey.

ENGAGEMENT DETAILS

Location Sydney, NSW (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