2 days ago

Forward Deployed Engineer, Scams

Australian Financial Complaints Authority

Melbourne

2 days ago

Apply

AFCA is seeking a Forward Deployed Engineer for its Scams Prevention Framework in Melbourne. The role embeds with business teams to rapidly solve operational challenges using software, AI, automation, and data solutions. Requires experience in software, solution, AI, or data engineering with strong stakeholder engagement skills.

Core AIHybridFull-timeSeniorSoftware EngineeringSolution Engineering

Forward Deployed Engineer, Scams

Apply

Core AIHybridFull-timeSeniorSoftware Engineering

Salary

Not specified

Work Location

Melbourne, Victoria, Australia, AU

Work Model

Hybrid working – Flexible arrangements with two days a week in our modern offices designed for collaboration and wellbeing.

Employment Type

Full-time

Experience Level

Mid-Senior level

Core Qualifications

Technical (Must-have)

Software EngineeringSolution EngineeringAI EngineeringData EngineeringCloud-based ApplicationsIntegrationsAIAutomationWorkflow TechnologiesAgileDevOpsCI/CD

Soft Skills

Stakeholder EngagementCommunicationProblem-solvingCommercial Mindset

Preferred Qualifications

Technical (Nice-to-have)

ServiceNowAPI IntegrationGenerative AIAI AgentsAutomation PlatformsMicrosoft AzureAI ServicesResponsible AIGovernanceSecurity

Key Responsibilities

•Work directly with business teams to identify high-value opportunities for automation, AI and digital enablement.
•Embed within operational teams to develop a deep understanding of processes, pain points and customer outcomes.
•Translate ambiguous business challenges into clear technical problems and potential solutions.
•Act as a trusted technical advisor to senior stakeholders.
•Design and build rapid prototypes, proofs of concept and production-ready solutions.
•Develop integrations across enterprise platforms including Optimizely, Microsoft, ServiceNow, Dynamics, Workday, Databricks, data platforms and AI services.
•Build scalable software, workflows and automation solutions that align with enterprise architecture standards.
•Apply modern engineering and DevOps practices across all solutions.
•Design and implement AI-enabled solutions using LLMs, agents, retrieval architectures and automation capabilities.
•Partner with data teams to leverage enterprise data assets effectively.
•Ensure AI solutions comply with governance, security and responsible AI requirements.
•Measure and demonstrate value delivered through implemented solutions.
•Capture recurring customer requirements and convert them into backlog items for core platforms and products.
•Influence platform roadmaps based on real-world user needs.
•Identify opportunities to standardise bespoke solutions into reusable enterprise capabilities.
•Rapidly iterate solutions based on user feedback.
•Support implementation, adoption and transition into operational support models.
•Provide technical leadership throughout the full solution lifecycle.

Forward Deployed EngineerScams PreventionFinancial ServicesAIAutomationData EngineeringSoftware EngineeringMelbourneFull-timeHybrid

Key Responsibilities

•Work directly with business teams to identify high-value opportunities for automation, AI and digital enablement.

•Embed within operational teams to develop a deep understanding of processes, pain points and customer outcomes.

•Translate ambiguous business challenges into clear technical problems and potential solutions.

•Act as a trusted technical advisor to senior stakeholders.

•Design and build rapid prototypes, proofs of concept and production-ready solutions.

•Develop integrations across enterprise platforms including Optimizely, Microsoft, ServiceNow, Dynamics, Workday, Databricks, data platforms and AI services.

•Build scalable software, workflows and automation solutions that align with enterprise architecture standards.

•Apply modern engineering and DevOps practices across all solutions.

•Design and implement AI-enabled solutions using LLMs, agents, retrieval architectures and automation capabilities.

•Partner with data teams to leverage enterprise data assets effectively.

•Ensure AI solutions comply with governance, security and responsible AI requirements.

•Measure and demonstrate value delivered through implemented solutions.

•Capture recurring customer requirements and convert them into backlog items for core platforms and products.

•Influence platform roadmaps based on real-world user needs.

•Identify opportunities to standardise bespoke solutions into reusable enterprise capabilities.

•Rapidly iterate solutions based on user feedback.

•Support implementation, adoption and transition into operational support models.

•Provide technical leadership throughout the full solution lifecycle.