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 across both data pipelines and AI systems to ensure reliability, accuracy, and supportability in production.
- Familiarity with real-time and event-driven architectures, vector databases, and data storage patterns spanning relational, NoSQL, and analytical platforms.
- Knowledge of data governance, privacy, and security practices, with the ability to embed Responsible AI and sound data management principles into engineering workflows.
- Strong collaboration and stakeholder engagement skills, with the ability to work across platform, data, AI, and business teams to deliver integrated solutions.
- A growth mindset with the ability to mentor others, contribute reusable engineering patterns, and help mature AirTrunk’s AI and Data engineering capability.
The AirTrunk Culture
Working at AirTrunk is a once in a lifetime opportunity to fast-track your career and amplify your impact. Whilst you’re helping scale our region’s digital future, we’ll help you Grow@Hyperscale and unleash your full potential.
The pace in which we operate means you’ll feel an electric atmosphere at AirTrunk. We are a team of challengers and collaborative problem solvers who break new ground every day. We do this by living our values, going above and beyond, and being dynamic, transparent, and responsive.
Every AirTrunker brings their own unique background and diverse perspective to find solutions to problems that matter. We make sure you have everything you need to make your mark and thrive in a flexible and safe working environment, where everyone feels welcome. Our benefits empower AirTrunkers to stay positively charged.
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EEO Statement
The Company is an equal opportunity employer. In accordance with applicable law, we prohibit discrimination against any applicant, employee, or other covered person based on any legally recognized basis, including, but not limited to: veteran status, uniformed servicemember status, race, color, caste, immigration status, religion, religious creed (including religious dress and grooming practices), sex, gender, gender expression, gender identity, marital status, sexual orientation, pregnancy (including childbirth, lactation or related medical conditions), age, national origin or ancestry, citizenship, physical or mental disability, genetic information (including testing and characteristics), protected leave status, domestic violence victim status, or any other consideration protected by federal, state or local law. We are committed to providing reasonable accommodations, if you need an accommodation to complete the application process, please email [email protected]