C

CreditorWatch

Accounts receivable platform for automated collections

AI Product Engineer

AI Application EngineeringUpdated on Nov 15
Full-timeSydney NSW, Australia

About the Job

Requirements

  • Proven experience designing, building, and operating production-grade AI systems, ideally in customer-facing or business-critical environments.
  • Solid software engineering, system design, and operational discipline, with the ability to build maintainable and scalable solutions.
  • Sound judgment across large language model architecture, retrieval-augmented generation, model orchestration, agentic workflows, and tool integration.
  • Experience with AI evaluation, observability, security, reliability, and the practical challenges of running AI systems in production.
  • An appreciation for reusable frameworks, shared capabilities, and developer experience rather than building one-off solutions.
  • Experience with Langfuse, MLflow, OpenTelemetry, Datadog, PostgreSQL, OpenSearch, vector databases, AWS, Docker, and GitHub.
  • Experience designing and operating agentic or multi-agent systems in production.
  • Practical experience with large language model evaluation, AI safety, governance, and compliance controls.
  • Experience building shared platforms, frameworks, or developer capabilities adopted across multiple teams.
  • Experience delivering technology in regulated or risk-sensitive environments.
  • A track record of mentoring, providing architecture direction, and driving cross-team engineering initiatives.

Responsibilities

  • Design, build, and operate AI products, application programming interfaces, retrieval-augmented generation solutions, and agentic workflows that solve customer and business problems.
  • Own complex AI initiatives end-to-end, from discovery and architecture through implementation, evaluation, deployment, and ongoing improvement.
  • Turn emerging AI capabilities into practical, reliable experiences that deliver measurable value.
  • Develop shared AI capabilities, reusable frameworks, and self-service patterns for model orchestration, prompt management, agent execution, and tool integration.
  • Establish engineering standards and best practices that help teams build and deploy AI consistently and at scale.
  • Influence the architecture and technical foundations underpinning the broader AI ecosystem.
  • Establish standards for AI testing, evaluation, observability, security, governance, and production reliability.
  • Build maintainable, scalable, and resilient solutions while balancing experimentation with sound engineering discipline.
  • Identify opportunities to improve performance, reliability, and cost across AI systems.
  • Partner with Product, Engineering, Data, and Infrastructure teams to turn business problems into effective technical solutions.
  • Provide architecture guidance, mentor engineers, and contribute to technical decision-making across teams.
  • Share knowledge, document patterns, and help increase AI engineering capability across the company.

Desired Qualifications

  • Experience designing, building, and operating production-grade AI systems in customer-facing or business-critical environments is preferred.
  • Experience with Langfuse, MLflow, OpenTelemetry, and Datadog is beneficial.
  • Experience with PostgreSQL, OpenSearch, and vector databases is beneficial.
  • Experience with AWS, Docker, and GitHub is beneficial.
  • Experience with agentic or multi-agent systems in production is beneficial.
  • Practical experience with large language model evaluation, AI safety, governance, and compliance controls is beneficial.
  • Experience building shared platforms, frameworks, or developer capabilities adopted across multiple teams is beneficial.
  • Experience delivering technology in regulated or risk-sensitive environments is beneficial.
  • A track record of mentoring, providing architecture direction, and driving cross-team engineering initiatives is beneficial.

About the Company

CreditorWatch

Accounts receivable platform for automated collections

CreditorWatch Collect automates accounts receivable work by helping finance teams prioritize the right overdue accounts, automate follow-ups, and collect payments all in one workflow. It combines AR automation with real-time risk signals from CreditorWatch data and built-in payments, so teams can act earlier, reduce manual effort, and protect customer relationships. The product sits within CreditorWatch and is trusted by thousands of businesses. Its goal is to improve cash flow and reduce the time and guesswork involved in chasing invoices without harming customer relationships.

Company size
201-500
Company stage
Not listed
Total funding
Not listed
Headquarters
Sydney NSW, Australia
Founded
2010

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