AI Developer at Qualitas

Melbourne, Victoria, Australia -

Full Time

Start Date

Immediate

Expiry Date

24 Aug, 26

Salary

0.0

Posted On

26 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, LLM Orchestration, Cloud Infrastructure, Data Pipelines, RESTful APIs, Async Patterns, API Frameworks, Relational Databases, Event-driven Integration, Software Development, Data Engineering, AI Automation, UAT, Technical Documentation, Operational Monitoring, Cost Management

Industry

Financial Services

Description

About Qualitas Qualitas is a leading ASX-listed Australian alternative real estate investment manager, specialising in real estate private credit and real estate private equity. For 18 years we have been helping our partners realise their vision and delivering attractive risk-adjusted returns to our investors. About the position This role works alongside the Process & Automation Lead within the Qualitas AI Transformation Office to turn redesigned workflows into production-grade solutions. You will build, test, deploy, and maintain AI-powered pipelines, integrations, automations, and data flows that the business relies on daily. Working across our full AI and automation stack, you are the person who makes things work. You will also serve as a key bridge between technology and the business, translating process redesigns into working solutions and supporting real user adoption. Location: Melbourne Employment Type: Permanent Full-time What you’ll do You’ll design, build, and maintain AI-powered workflows end-to-end from LLM orchestration and evaluation frameworks through to cloud infrastructure, data pipelines, and business system integrations. This includes standing up robust testing, monitoring, and deployment practices to keep production workloads reliable and cost-effective. You’ll also work directly with business users to translate process redesigns into technical solutions, run UAT, gather feedback, and iterate until adoption lands. Maintaining clear documentation, reusable components, and sensible automation choices is part of the day-to-day. What you’ll bring to the role 5+ years in software development, data engineering, or AI/automation roles with demonstrated experience building and deploying LLM-powered applications Strong Python development including async patterns, API frameworks, data libraries, and testing Hands-on experience deploying and operating AI workloads on a major cloud platform, including configuration, cost management, and operational monitoring Comfortable working with RESTful APIs, authentication protocols, event-driven integration patterns, relational databases, and data pipelines Proven end-to-end ownership from requirements through production deployment and user adoption; experience working directly with business users, not purely in engineering silos Degree in Computer Science, Software Engineering, Data Science, Mathematics, or equivalent practical experience; a portfolio of relevant work carries equal weight Strong written and verbal communication; able to explain technical decisions to non-engineers and document work clearly We recognise that our people are our greatest strength and as an equal opportunity employer, we are committed to celebrating diversity and fostering an inclusive and equitable workplace where all employees are empowered to thrive. Apply now This is a unique opportunity to shape how AI is built and adopted across Qualitas. If you thrive at the intersection of engineering and business impact, we’d love to hear from you. Please submit your resume along with a short note (no more than 300 words) describing a specific AI or automation solution you built, the problem it solved, and one thing you’d do differently in hindsight. We encourage candidates from all backgrounds to apply for this role and do not discriminate on the basis of age, sex, nationality, race, ethnicity, gender identity or expression, sexual orientation, veteran status, marital status, family status, pregnancy, religion, beliefs, neurodiversity or disabilities.

Responsibilities

Design, build, and maintain end-to-end AI-powered workflows and production-grade pipelines. Act as a bridge between technology and business users to translate process redesigns into working solutions.