Forward Deployed Engineers are the engineering core of Avanade Next. They sit inside the client from week one and turn business ambition into production reality — proving the direction in Consulting with a working prototype, leading the build in Studios, and configuring products for client environments. They work alongside business stakeholders, Industry Reinvention Leads, Domain Architects, Value Architects and Trust Architects to understand what matters commercially, then build the system that delivers it.
This is not a order-taking role. Forward Deployed Engineers help clients decide what should be built, challenge assumptions where the value is not there, and lead the work through to live deployment. They work in small expert teams directing agent networks rather than large delivery pyramids, and they carry accountability from the first brief through to production — which is unusual, and is the point.
Location: Flexible across Sydney, Melbourne, Brisbane, and Perth.
KEY RESPONSIBILITIES
Client Partnership & Problem Framing
Work with clients, Industry Leads, Domain Leads, Value Architects and Trust Architects to understand business priorities.
Shape solutions that are commercially viable, technically feasible and production-ready.
Operate with autonomy in ambiguous client environments.
Build & Deployment
Build and deploy agentic AI systems end-to-end.
In Consulting, build prototypes that prove strategy is real.
In Studios, take use cases from prototype to production-grade systems.
In Products, configure and deploy pre-built products into client environments.
Technology & AI-Native Practice
Design on the Avanade Agentic Platform and Microsoft AI stack.
Apply agent-assisted development, automated evaluation, observability and production operations.
Work with Trust Architects so evaluation, accuracy and guardrails are built in.
Reuse & Contribution
Contribute reusable components, patterns and assets from every engagement.
Work with Value Architects to keep delivery tied to measurable outcomes.
Carry context across phases so learning compounds.
Client outcomes achieved through production deployments, evidenced by business value realised and client referenceability
Production-grade delivery on every engagement; no prototype handed over without a production path.
Demonstrable productivity through AI-native engineering practices and agent utilisation.
Reusable assets contributed to the library from every engagement.
Accuracy and evaluation thresholds met before release.
