Senior AI Engineer
Confirmed on the employer's own hiring board on Nov 14, 2026. First seen by Alion on Nov 13, 2026.
See yourself being part of a large, transformational change? This could be the role for you!
At Iress, we make things happen
Opening the world to financial opportunity.
At Iress, we believe more people should have the chance to build a better financial future. That's why we build and connect the infrastructure that powers global markets, simplifying the complex so systems run smarter, institutions move faster and progress reaches further.
We equip financial professionals and institutions with the tools and systems they need to scale services, reach more people, embrace new ways of working, and shape the future of financial services.
Iress is a technology company providing software to the financial services industry. We have 1,100+ people across Asia Pacific, the United Kingdom, South Africa and Canada. Our award-winning technology is used by businesses and people around the world to help them perform better and deliver more.
Build your career at Iress!
Join Iress at a pivotal point in the evolution of our products. As we shape what’s next for Xplan, you’ll build the shared AI foundations that help teams deliver useful, trustworthy AI experiences across a leading wealth platform.
This is production AI-not a lab for proofs of concept. You’ll design, build and operate AI capabilities that real teams and customers can rely on, from agents and Xplan integrations to evaluation, retrieval, guardrails and observability. Based in Sydney or Melbourne, you’ll work across Engineering, Product and Data, helping establish the patterns and standards for AI at Iress.
Some of the amazing things you’ll be involved in
- Building and operating shared AI platform capabilities, including agent runtimes, tool and Xplan API integrations, AI gateways, guardrails and privacy-conscious data handling.
- Creating evaluation frameworks, golden datasets, regression tests and release quality gates to measure AI behaviour before and after release.
- Improving prompts and context, investigating inconsistent model responses, and troubleshooting failures to make results more reliable.
- Establishing production practices for tracing, monitoring, reliability, latency and cost-and responding to changes in model behaviour.
- Partnering with Data teams on retrieval-augmented generation (RAG), data pipelines and retrieval capabilities with appropriate access controls and audit trails.
- Making capabilities easy for other teams to adopt through reusable APIs, SDKs, reference implementations, documentation and hands-on support.
- Working with Product, domain experts and engineering teams to understand needs, explain trade-offs and deliver secure, measurable AI experiences.
What you will bring
- Hands-on experience building, deploying and operating LLM- or agent-based systems in production. Personal projects and proof-of-concept work alone won’t be enough for this role.
- Strong software engineering fundamentals and practical experience with Python and/or TypeScript, including API development or reusable engineering patterns.
- Experience evaluating AI-generated outputs with systematic methods such as evaluation frameworks, golden datasets and regression testing-not subjective checks alone.
- Practical prompt and context engineering skills, and the ability to investigate model behaviour, explain what went wrong in production and how you improved it.
- An understanding of the real-world demands of production AI, including performance, latency, reliability, failure handling and cost.
- Experience building and operating production software, with a clear approach to observability, privacy, access controls and auditability.
- The communication and collaboration skills to explain AI limitations, risks and trade-offs to both technical and non-technical teams.
You might be a Senior Software Engineer, Backend Engineer, AI Platform Engineer or an AI/Data Engineering hybrid. Your industry background matters less than your engineering foundations and proven production AI experience. Experience with RAG, vector search, PII handling, Databricks or data pipelines would be an advantage.
Why work with us?
- 8 additional paid days per year to extend your weekends
- Hybrid working
- Generous cash bonus for every successful referral
- Starting school leave - 8.5 days of leave to assist your children with the transition to school
- Up to 26 weeks’ paid parental leave for primary carers (up to 4 weeks for secondary carers), and the ability to work part-time when returning to work
- 3 days’ paid leave per year to participate in charity initiatives
- Discounted health insurance premiums
- Access to learning and development programs through LinkedIn Learning
Inclusion
Iress is committed to fostering a welcoming and inclusive culture. We strongly believe that diversity is what makes our teams and our products succeed. Our people have different experiences, skills, perspectives and beliefs, and everyone’s uniqueness is valued and celebrated.
Our hiring decisions are never based on sexual orientation, race, gender identity, religion, disability, citizenship, marital or family status, or age. Even if you feel you don’t meet all of the requirements of the role, we would still like to hear from you!
We’re also proud to be globally recognised as a WORK180 Endorsed Employer that promotes and supports all women in the workplace.
For more information about what we do, our people and values, please visit Iress Careers.