Software Engineer - AI

Betashares; Sydney; On-site; AUD 110,000 - 170,000; Full time

Job summary

Betashares is hiring a Software Engineer to build our internal AI Platform, powering Agentic AI use cases across the organisation. This frontend-heavy role focuses on crafting intuitive interfaces while also bringing backend competencies for platform services and integrations.

You’ll work with designers, business users, and platform engineers to deliver AI-native experiences company-wide, with hands-on execution and a bias toward continuous improvement across our AI ecosystem.

Qualifications

• Strong frontend engineering fundamentals with TypeScript/React techniques.
• Experience with AI tooling and patterns in development workflows.
• Experience with Agentic AI: LLM apps, multi-agent patterns, tool use or AI orchestration.
• Ability to translate ambiguous business requirements into concrete UI specs.
• Comfort across UI polish and platform architecture decisions.

Responsibilities

• Design and build AI interfaces and interaction patterns for the internal platform and business applications.
• Own frontend architecture for AI-powered features and contribute to backend APIs and integrations.
• Collaborate with designers to establish UI/UX standards for complex AI interactions.
• Prototype interfaces for AI use cases and iterate with business users.
• Connect frontend experiences with backend AI infrastructure and tools.
• Test AI features and optimize user experience for staff.

Skills

TypeScript/React

AI tooling experience

Agentic AI

UX collaboration

Full-stack familiarity

Job description

Betashares is hiring a Software Engineer to build our internal AI Platform powering Agentic AI use cases across the organisation. This is a frontend-heavy role where you’ll craft the interfaces and interaction patterns that make AI capabilities accessible while also bringing backend competency to architect platform services and integrations.

You’ll work directly with designers, business users, and platform engineers to deliver AI-native experiences that serve teams company-wide. This role is hands-on, with a strong focus on execution, while also contributing to user-centred thinking and continuous improvement across our AI ecosystem.

Role Responsibilities

• Design and build AI interfaces and interaction patterns for the internal platform and business applications, translating complex agentic workflows into intuitive, performant user experiences.
• Own frontend architecture for AI-powered features while contributing to platform backend capabilities, including but not limited to, APIs, backend architecture, and integrations that enable agentic functionality.
• Partner with designers to establish UI/UX standards that enable complex AI interactions.
• Work with business users to understand specific AI use cases, rapidly prototype interfaces, and iterate on tools that make agentic AI accessible to non-technical stakeholders.
• Collaborate with engineers to connect frontend experiences with backend AI infrastructure.
• Test the AI capabilities you build and leverage AI tooling to accelerate platform development while refining the user experience for staff.
• Maintain operational excellence across the AI platform stack with administrative control panels and dashboards: ensure AI platform operations are readily manageable at enterprise scale.

Key skills and experience

• Strong frontend engineering fundamentals with TypeScript/React expertise and a portfolio of complex, interactive applications.
• Hands-on familiarity with AI interaction patterns and a proven track record of leveraging AI tooling heavily in your development workflow is highly valued.
• Experience with Agentic AI: LLM application development, multi-agent patterns, tool use, retrieval-augmented generation, or AI workflow orchestration.
• Track record of collaborating with designers on UX patterns, and ability to translate ambiguous business requirements into concrete interface specifications.
• Comfort working across the stack and context-switching between UI polish (animation, accessibility, state management) and platform architecture decisions (data models, service boundaries).
• Strong communication skills, ability to teach AI literacy, and patience for working with business users who may be early in their AI adoption journey.
• Experience in financial services or regulated environments is a plus, but not essential.