AI Automation Engineer

• Design and build LLM-powered features and automation workflows including RAG pipelines, agent workflows, and tool-calling integrations
• Contribute to data-flow design, context management, and model selection decisions
• Participate in technical design reviews and help establish good patterns for prompt engineering, retrieval, and output validation
• Lead the development of AI tools and applications, from inception to implementation
• Identify and address quality issues in production AI systems
• Help migrate ad-hoc LLM integrations toward more maintainable, testable service boundaries
• Flag and help address technical debt in AI workflows
• Implement and contribute to evaluation frameworks for AI systems in production
• Instrument AI features with meaningful observability: token consumption, latency, retrieval quality, and error rates
• Help define quality baselines and monitor AI system performance over time
• Build AI features in line with Brighte's data handling policies and relevant regulatory requirements (Australian Privacy Act, CDR, APRA CPS 234)
• Work with Risk and Compliance stakeholders to ensure AI-influenced decisions are appropriately logged and explainable
• Apply security best practices including PII redaction and prompt injection awareness
• Collaborate closely with product, data, and engineering peers to deliver AI features
• Share knowledge of AI design patterns with the team
• Provide thoughtful code reviews and contribute to engineering best practices for AI systems

• 5+ years of software engineering experience
• At least 2 years building and operating LLM or AI-powered systems in production
• Experience working in a fintech, lending or payment business is highly advantageous
• Solid understanding of LLM integration patterns: RAG architecture, prompt engineering, embedding models, vector databases, and output validation
• Hands-on experience with workflow automation platforms (n8n, Temporal, or similar) in a production context
• Working knowledge of AWS Bedrock, or experience integrating multiple LLM providers
• Awareness of AI compliance considerations in regulated environments, data handling, audit logging, and explainability basics
• An AI-first mindset, proactively looking for opportunities to apply AI thoughtfully and evaluating model outputs critically

Experience working in a fintech, lending or payment business

• Flexible working arrangements
• Hybrid work model (3 days in office, 2 WFH)
• Free lunch on Mondays
• Weekly Thursday social event
• Employee Share Option Plans (ESOP)
• Stocked pantry with snacks
• Fresh bread
• Protein bars
• Popcorn
• Fresh fruit
• Chocolate
• Soy crisps
• Cookies
• Curated collection of wines and beer on tap
• End-of-trip facilities with towel service and hair dryers
• Anniversary leave