AI Architect - Databricks

Unison Group; City of Brisbane; On-site; AUD 180,000 - 240,000; Full time

Job summary

Unison Group is seeking an experienced AI Architect to design and lead scalable AI/ML platforms across enterprise data solutions. The role focuses on Databricks Lakehouse, end-to-end AI/ML lifecycle, and governance, partnering with data engineers, scientists, and cloud teams.

You will define enterprise AI architecture, drive data/AI transformation, and translate business use cases into production-ready AI solutions with strong emphasis on RAG, vector stores, and generative AI integrations.

Qualifications

• 8–15 years of experience in Data/AI/Analytics architecture for enterprise-scale implementations.
• Hands-on Databricks experience with Lakehouse, Delta Lake, Unity Catalog and MLflow.
• Strong Python, PySpark and SQL for AI/ML solution development.
• Experience with MLOps/LLMOps, CI/CD, model registry and deployment.

Responsibilities

• Design and implement enterprise AI/ML architecture using Databricks Lakehouse Platform.
• Define scalable data ingestion, feature engineering, model training and deployment.
• Architect and optimize AI/ML pipelines with Databricks, Spark, Python, SQL and cloud services.
• Lead MLOps/LLMOps frameworks for model lifecycle management and governance.
• Collaborate with stakeholders to identify AI/ML use cases and prioritize accordingly.
• Build architectures for LLM/Generative AI including RAG, vector stores and embeddings.
• Establish best practices for data quality, security, observability, and responsible AI.
• Provide technical leadership in tool selection and cloud service alignment.

Skills

Databricks

Data Engineering

Machine Learning

Cloud-based AI

Python

PySpark

SQL

MLOps

LLMOps

Cloud Platforms (Azure AWS GCP)

Tools

Databricks Lakehouse

Delta Lake

Unity Catalog

MLflow

Databricks Workflows

Job description

We are looking for an experienced AI Architect with strong expertise in Databricks, Data Engineering, Machine Learning, and Cloud-based AI solutions to lead the design and implementation of scalable AI/ML platforms and intelligent data solutions. The ideal candidate will define enterprise AI architecture, drive modern data and AI transformation initiatives, and work closely with business, engineering, and analytics teams to deliver high-impact solutions.

This role requires a strong understanding of end-to-end AI/ML lifecycle, Lakehouse architecture, Databricks ecosystem, and the ability to translate business use cases into production-ready AI solutions.

Key Responsibilities

• Design and implement enterprise AI/ML architecture using Databricks Lakehouse Platform.
• Define scalable solutions for data ingestion, feature engineering, model training, deployment, monitoring, and governance.
• Architect and optimize AI/ML pipelines using Databricks, Spark, Python, SQL, and cloud-native services.
• Lead the setup of MLOps / LLMOps frameworks for model lifecycle management, CI/CD, model registry, and automated deployment.
• Work with business stakeholders to identify and prioritize AI/ML use cases, including predictive analytics, NLP, recommendation engines, and generative AI.
• Build and guide architecture for LLM / Generative AI solutions, including RAG, vector databases, prompt orchestration, and model integration where applicable.
• Establish best practices for data quality, security, compliance, observability, scalability, and responsible AI.
• Collaborate with Data Engineers, Data Scientists, Product Owners, and Cloud teams to ensure solution alignment with enterprise architecture standards.
• Provide technical leadership in selecting AI/ML tools, frameworks, and cloud services aligned to business and platform strategy.
• Support architecture reviews, technical design workshops, PoCs, and enterprise AI roadmap planning.

Required Skills & Experience

• 8- 15 years of experience in Data / AI / Analytics architecture, with strong exposure to enterprise-scale implementations.
• Hands-on experience with Databricks including:
• Databricks Lakehouse
• Delta Lake
• Unity Catalog
• MLflow
• Databricks Workflows
• Model Serving / Feature Store (preferred)

Strong programming experience in Python, PySpark, SQL, and AI/ML solution development. Solid experience in designing and deploying Machine Learning pipelines in production. Good understanding of MLOps / LLMOps, including model versioning, CI/CD, deployment, monitoring, and governance. Experience with cloud platforms such as Azure, AWS, or GCP, preferably with Databricks integration. Familiarity with Generative AI / LLM ecosystems, such as OpenAI, Hugging Face, LangChain, vector stores, embeddings, and RAG architectures. Strong understanding of data engineering, ETL/ELT, distributed computing, and data platform modernization. Experience in solution architecture, technical governance, and stakeholder engagement.