Principal Forward Deployment Engineer

Candidate Description

Specialising in production AI and enterprise data platforms, the candidate brings more than 10 years of software development experience and hands-on principal engineering capability. They currently work as a Principal Forward Deployment Engineer with a technology company, delivering solutions from architecture and implementation through evaluation and operational handover. Their core expertise spans multi-agent systems, retrieval-augmented generation, GPU-accelerated inference and warehouse-scale Microsoft Fabric migrations across Azure and AWS. Their delivery experience includes healthcare, enterprise facilities services, education, beauty-product innovation, logistics and accounts-payable/procurement software. They combine full-stack development with cloud infrastructure, data engineering, Dynamics 365 Customer Engagement and Finance & Operations integration, and rigorous production validation.

End-to-end ownership is demonstrated by their delivery of a healthcare provider's clinical billing intelligence system solo in under 10 weeks, ahead of schedule and under budget. The solution achieved 88% precision with zero rule violations on the clinician-signed evaluation set and projected more than $1 million in annual recovery. For an enterprise facilities services company, they migrated a SQL Server estate to Microsoft Fabric in approximately two months, reduced transformation cycles from a 3.8-hour average to 34–57 minutes, and delivered repeatable acceptance evidence and operational handover. Their broader AI toolkit includes GPT-5/GPT-4, Amazon Bedrock, LangGraph, LangChain, LlamaIndex, hybrid/vector search, HyDE, RRF, CRAG, MMR, knowledge graphs, ChromaDB and Giskard. They also bring PyTorch, TensorFlow, XGBoost, reinforcement learning, CUDA, cuDNN and TensorRT expertise, complemented by Python, C++, C#, Golang, TypeScript and JavaScript. Cloud and data delivery capabilities encompass Azure Container Apps, AWS SageMaker, Lambda, Kendra, Microsoft Fabric Warehouse/Lakehouse, OneLake/Delta, CDC, SQL Server, PostgreSQL, MongoDB, DynamoDB, Redis, Bicep, Terraform, Kubernetes, Azure DevOps, GitHub Actions and OpenTelemetry.

Their progression from Full Stack/AI/ML Developer to Head Engineer at a technology company reflects growing responsibility for architecture and engineering leadership. At an AI consulting firm, they delivered multi-agent innovation workflows adopted by leading beauty brands, increased model throughput by 40% and reduced false matches by 30%. At a logistics technology company, their forecasting, document extraction and conversational AI work improved operational accuracy and customer experience. They collaborate with clinical subject-matter experts and enterprise stakeholders, combining human review, privacy controls, automated testing and knowledge transfer to support dependable adoption. Their contribution to an internal Gen-AI accelerator and delivery for a scholarship program and a rail operator demonstrate adaptability across client needs and technology environments. An Australian citizen based in Melbourne and available in two weeks, they offer a combination of technical depth, independent delivery and accountable production ownership.