Enterprise AI Data Architect & MLOps Leader

Overview

We seek a strategic and hands-on AI Data Architect experienced in designing and scaling enterprise AI platforms, data lakes, and MLOps within cloud environments. The successful candidate will bridge large-scale data engineering with production-ready machine learning and Generative AI technologies, including retrieval-augmented generation (RAG), foundation models, agentic workflows, and secure enterprise integration.

Key Responsibilities and Role Impact

You will contribute significantly by shaping cutting-edge AI and data architectures, establishing scalable design patterns, and driving advanced enterprise solutions from proof-of-concept through to full production deployment.

Required Expertise and Experience

• Proven proficiency with end-to-end machine learning lifecycle and MLOps platforms, such as SageMaker, Azure Machine Learning, Google Vertex AI, Databricks Machine Learning, or Mosaic AI.
• Hands-on experience developing Generative AI applications, RAG implementations, agent-based solutions, or large language model-powered features using platforms like Bedrock, Microsoft Foundry, Vertex AI, Databricks Mosaic AI, OpenAI, or Anthropic.
• Demonstrated ability to design scalable enterprise data platforms including data lakes, lakehouses, and object storage on AWS, Azure, Google Cloud, Databricks, or Snowflake.
• Experience constructing complex ETL/ELT pipelines integrating diverse enterprise systems with cloud-native, commercial, or open-source data engineering tools.
• Expertise processing large-volume datasets with distributed computing frameworks such as Apache Spark, Hadoop, or Databricks.
• Skill designing real-time streaming and event-driven systems using technologies like Apache Kafka, Confluent, Event Hubs, or Google Pub/Sub.
• Background working with cloud data warehousing and analytics platforms including Snowflake, BigQuery, Microsoft Fabric, Azure Synapse, or Databricks.
• Knowledge implementing serverless and data lake analytics to enable SQL-based and distributed query analytics on massive cloud datasets.
• Experience selecting and managing relational and NoSQL databases such as PostgreSQL, MySQL, Oracle, MongoDB, Cassandra, Cosmos DB, or DynamoDB.
• Familiarity deploying enterprise data governance, cataloging, lineage, and access controls via Microsoft Purview, Unity Catalog, Collibra, Alation, or Dataplex.
• Capability transforming complex data into business insights using BI and visualization tools like Power BI, Tableau, Looker, Qlik, or QuickSight.

About Valrose and Working Culture

Valrose prioritizes listening to and understanding candidates to match their skills and aspirations in rewarding roles. We emphasize alignment with your financial goals, career development, culture preference, and technology interests, guiding you throughout the recruitment journey. Our ethos values humanity, success, integrity, accountability, curiosity, and fosters a diverse and inclusive workplace where authenticity is embraced as a driver of innovation.

We are recognized with multiple industry awards including the 2024 Sourcr Award for Best ICT Agency in WA and are committed to responding to every applicant as part of our Circle Back Initiative.