Data Scientist

Role Summary

We are seeking an AI/LLM Engineer to design, develop, and optimise intelligent document extraction solutions using Large Language Models (LLMs) and Azure AI services. You will build scalable AI pipelines, integrate enterprise data platforms, and develop production-ready solutions that deliver accurate, traceable, and auditable document processing.

Key Responsibilities

Design, develop, and maintain AI-powered document extraction pipelines using Python and LLMs.

Build durable, scalable workflows for document classification, extraction, and validation.

Develop prompt engineering strategies and structured outputs using Pydantic.

Implement automated validation, business rules, and data quality checks.

Extract, transform, and map document data into enterprise schemas while maintaining data lineage.

Integrate AI solutions with SAP, Snowflake, Cosmos DB, and other enterprise platforms.

Monitor, evaluate, and optimise model performance, accuracy, and reliability.

Develop evaluation frameworks, datasets, and performance metrics for AI models.

Collaborate with cross-functional teams to deliver secure, scalable, and production-ready solutions.

Maintain technical documentation and engineering best practices.

Required Skills & Experience

Strong Python development experience with production-quality, well-tested code.

Hands-on experience building LLM applications, including prompt engineering and structured outputs.

Experience designing AI evaluation frameworks, performance metrics, and model validation.

Experience with Azure AI services, including Azure OpenAI and Document Intelligence.

Strong SQL and data processing skills using Pandas or equivalent.

Experience with Git, code reviews, and CI/CD pipelines.

Knowledge of secure software development and enterprise data handling.

Excellent analytical, problem-solving, and communication skills.

Desirable Skills

Experience with Snowflake, Cosmos DB, and SAP (OData) integrations.

Retrieval-Augmented Generation (RAG) and recommender systems.

MLflow, Azure Machine Learning, and MLOps practices.

Streamlit, Power BI, OpenTelemetry, and Grafana.

GitLab CI/CD and AI-assisted development tools.

Technology Stack

Programming: Python, Pydantic, Pandas

AI & Machine Learning: Azure OpenAI, Azure Document Intelligence, Azure Machine Learning, MLflow

Cloud: Microsoft Azure Functions

Data: SQL, Snowflake, Cosmos DB, SAP OData

Visualisation & Monitoring: Streamlit, Power BI, OpenTelemetry, Grafana

DevOps: GitLab CI/CD, Git

Methodologies: Agile, CI/CD, AI/LLM Engineering, MLOps

Pay: From $120,000.00 per year

Work Location: Hybrid remote in Perth WA