Lead the technical strategy and architectural direction for Group AI Enablement, connecting enterprise AI ambitions with the engineering foundations needed to deliver them.
Locations (2)
Sydney, New South Wales, Australia
Melbourne, Victoria, Australia
Responsibilities
Define the long-term engineering strategy and architecture for enterprise AI capabilities.
Shape how AI models, agents, knowledge sources and business systems integrate, establishing patterns that enable security, interoperability and reuse.
Lead complex engineering initiatives from discovery and experimentation through to production.
Build reusable services, reference implementations and engineering patterns covering identity, permissions, observability and operational ownership.
Establish rigorous approaches to evaluating RAG and agentic systems using representative business tasks and measurable success criteria.
Manage a portfolio of top-tier accounts, accelerating product usage through strategic AI adoption in complex, large-scale environments.
Perform technical reviews for complex, large-scale systems, and ensure adherence to OutSystems development best practices.
Design technical adoption plans to drive strategic business impact by guiding customers to implement agentic systems that maximize platform value.
Guide customer development teams through the transition from standard applications to Agentic Workflows, leveraging OutSystems Mentor and Agent Workbench to drive significant business impact.
Serve as a customer advocate internally, interfacing with Product Management and Global Support to resolve challenges.
Requirements
Bachelor’s degree in a science or technical field, engineering, or computer science
Technical lead for the AI Enablement team, driving high-impact AI use cases from concept through production, establishing scalable architectures, and mentoring engineers.
Compensation
The expected salary/wage range for this position is provided below: 178,000-361,000
Responsibilities
Lead lighthouse use cases end-to-end
Independently own high-impact AI use cases from problem framing and solution design through production deployment
Design the architecture of AI systems for scalability, performance, reliability, security, and supportability
Establish evaluation, guardrails, monitoring, documentation, and performance metrics
Create reusable patterns, reference architectures, and tooling
The Lead Applied Scientist is the senior scientific authority in the Data Science and AI Delivery team, responsible for the quality of the AI the team produces, particularly using large language models and agentic approaches. The role leads work from problem framing through build to evaluation production monitoring.
Compensation
competitive target incentive compensation, with awards based on overall corporate and individual performance.
Responsibilities
Lead the team's approach to solving business problems through advanced analytics and AI
Guide how solutions are designed and built
Contribute directly to technical work such as model development, experimentation, code review and solution architecture
Lead the design and development of AI and ML solutions using large language models and agentic AI
Bring mathematical and statistical rigor to how problems are framed and how uncertainty is handled
Requirements
Postgraduate qualification in a quantitative or computational subject such as computer science, statistics or mathematics
As a Forward Deployed Engineer Intern, you'll work directly with customers and the founding team to deliver real business impact by building workflow engines, data models, and AI-powered applications.
Responsibilities
Join customer calls to understand toughest challenges
Collaborate with founders and engineers to architect solutions
Deploy products to production and monitor customer use
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