Sr. Associate - AI and Data Engineer

Senior AI and Data Engineer Want to be a part of Asia Pacific & Japan’s (APJ) largest, most innovative, and rapidly growing data centre company?

AirTrunk is a technology company with a powerful purpose - to scale and sustain the relentless growth of the region’s digital future.

We do this by continuously redefining and delivering hyperscale data centres that meet the needs of our customers - the world’s most transformational companies.

And we’re doing so sustainably, for today and tomorrow.

Having opened Australia’s first and largest hyperscale data centres in 2017, we set our eyes on rapid expansion and now operate a platform of hyperscale data centres across the APJ region.

With backing from our investors, including Blackstone, this is just the beginning… Come join the A-Team at AirTrunk, where the cloud meets the ground.

A Snapshot As a Senior AI and Data Engineer at AirTrunk, you will help design, build, and operate the intelligent data and AI systems that power our next-generation data and AI platforms.

You’ll work at the intersection of data engineering, AI engineering, DevOps, and agentic automation, developing and deploying robust solutions that drive operational efficiency, sustainability, and intelligent decision-making across our data centre and business ecosystem.

This role is ideal for an engineer who thrives in a full-stack, DevOps-oriented environment and is passionate about shaping production-grade AI systems and modern data foundations that directly enable smarter, faster, and more efficient business outcomes.

You will help build both the data platform capabilities and intelligent applications that underpin AirTrunk’s AI and Data Platform.

Your Day to Day AI Engineering & Architecture Design, develop, and deploy scalable AI and ML solutions that enhance AirTrunk’s operations, from energy optimisation and predictive maintenance to intelligent automation.

Engineer agentic AI systems including multi-agent architectures, retrieval-augmented generation (RAG), and Model Context Protocols (MCPs) that enable adaptive, autonomous solutions.

Integrate emerging LLM and generative AI technologies (e.g.

Databricks, OpenAI, Anthropic, LangChain) into enterprise systems and data platforms.

Champion design standards and reusable patterns for AI components, tooling, and frameworks that ensure reliability, scalability, and security.

Data Engineering & Platform Foundations Design, build, and optimise robust batch and streaming data pipelines that support analytics, operational workloads, and AI use cases.

Develop and maintain curated, high-quality data models and datasets that enable trusted reporting, data products, and AI solutions.

Collaborate closely with platform engineers and data teams to integrate AI services into the broader AI & Data Platform ecosystem (Databricks, dbt, Kafka, Azure Event Hubs / Event Grid).

Improve data quality, lineage, observability, and discoverability through strong engineering standards, testing, and metadata practices.

MLOps, DataOps & Platform Integration Implement end-to-end MLOps pipelines including training, deployment, monitoring, and model lifecycle management across applications like Azure and Databricks.

Standardise and automate CI/CD pipelines for AI/ML workloads using Git, Terraform, Docker, and Kubernetes.

Implement robust observability and validation frameworks to ensure performance, accuracy, and reliability of AI models and agents as well as the resilience and supportability of data pipelines.

Contribute to the ongoing evolution of AirTrunk’s AI & Data Platform, enabling scalable experimentation, production delivery, and platform adoption.

Responsible AI & Innovation Embed Responsible AI practices through governance, ethics, and compliance with data privacy standards.

Experiment with emerging agentic AI technologies to extend platform intelligence and observability while maintaining transparency and trust.

Apply sound data governance, security, and privacy practices to data engineering and AI workflows alike.

Contribute to platform data classification and PII management practices, ensuring sensitive data is handled appropriately across structured and unstructured workloads.

Collaboration & Mentorship Collaborate cross-functionally with AI, Data and the broader technology team to deliver integrated, production-ready solutions.

Mentor junior engineers, fostering a culture of quality, learning, and operational excellence.

Actively contribute to AirTrunk’s Data & AI community of practice by sharing knowledge, reusable components, and engineering improvements.

Requirements 5 to 7 years’ experience in data engineering, AI/ML engineering, or software engineering, with proven delivery of production-grade data and AI solutions in cloud environments.

Demonstrated ability to architect scalable, high-performance, and secure data and AI solutions that meet enterprise standards.

Strong experience designing, building, and maintaining robust batch and streaming data pipelines, with hands-on knowledge of modern data engineering patterns and practices.

Experience developing and maintaining curated data models and datasets, with familiarity in medallion architecture, lakehouse concepts, and transformation frameworks.

Hands-on experience with Azure and Databricks preferred, and proficiency with data pipeline and streaming technologies including dbt, Kafka, and Azure Event Hubs.

Strong programming skills in Python, with proficiency in SQL and experience using JavaScript or Shell in engineering workflows.

Experience building and deploying AI/ML solutions, including LLM-based applications, intelligent automation, or agentic systems using platforms and tools such as OpenAI, Databricks, Anthropic, and LangChain.

Strong understanding of MLOps and DataOps practices, including CI/CD, testing, monitoring, orchestration, containerisation (Docker/Kubernetes), and infrastructure as code (Terraform).

Experience implementing observability, validation, and quality controls acr