Senior Software Engineer - ML & AI (AI Products)

Location: Hybrid in Sydney or Melbourne, Australia, with expected office days and collaborative boost days.

Company

hirify.global develops products and AI-powered financial workflows for small businesses.

What you will do

• Design, build, and own production services, pipelines, and infrastructure behind LLM-driven and agentic AI features.
• Build and operate platforms supporting traditional ML, generative AI, and agentic systems at scale.
• Develop capabilities for conversational AI, intelligent financial workflows, automated bank reconciliation, smart document capture, and AI-powered product workflows.
• Partner with Applied Scientists to move models into production and own the reliability, cost, scale, and performance of shipped systems.
• Set engineering standards, mentor engineers, and improve data usability and system dependability across AI Products.

Requirements

• Track record of designing, shipping, and operating production-grade backend systems at scale.
• Experience building and operating production systems for LLM or agentic workloads, including orchestration, tool use, evaluation, guardrails, latency, and cost management.
• Strong system design fundamentals and excellent coding in Python or another language suited to web-scale services, such as Go, Java, Kotlin, or TypeScript.
• Experience with APIs, service design, cloud infrastructure, ideally AWS, CI/CD, and observability, with focus on latency, cost, reliability, and SLOs.
• Experience running services in production, including on-call and incident response.
• Solid SQL skills and experience with large-scale data processing.
• Excellent communication skills for explaining complex technical concepts to business and technical audiences.
• Coaching mindset and ability to set engineering standards and mentor other engineers.

Nice to have

• Experience operationalizing ML or LLM workloads, including inference serving and evaluation pipelines.
• Familiarity with MLflow, PyTorch, TensorFlow, and data orchestration tools.
• Distributed processing experience with Spark or Dask.

Culture & Benefits

• Flexible hybrid work model combining office collaboration with remote-work autonomy.
• Modern office spaces and team-aligned office and boost days.
• Collaboration with scientists, engineers, product managers, and analysts in a globally distributed AI team.
• Opportunities to improve engineering capability through mentoring and setting standards.

Hiring process

• Applications are encouraged even when experience is not a perfect match; assessment focuses on skills, passion, and the perspective brought to the team.