Principal Software Engineer – AI & ML Platform

Atlassian’s mission “to unleash the potential of every team” is the guiding light behind what we do. We have developed well-known products such as Jira, Confluence and Bitbucket, that fit into the fabric of teamwork across different types of teams and the processes to help every team succeed.

Atlassian helps teams everywhere change the world. Our products are revolutionising the software industry, and helping teams collaborate and create the magic that provides their best work. Think NASA launching the Rover on Mars or Cochlear gifting those born deaf with the ability to hear, your work directly impacts the products they use to promote humanity.

About Central AI Org:

Our organisation is designed to accelerate AI innovation across all our products and platform, provide cohesive AI experiences and setup up an Atlassian AI infrastructure for the future. Our purpose is to:

• Build horizontal AI capabilities and infrastructure which provides leverage across products
• Build a centralised Search, Q&A and Conversational AI across all Atlassian products.
• Explore integration of Atlassian products with AI products outside Atlassian.

About AI & ML Platform Team:

Our team is building the foundations to democratise Machine Learning for Atlassian’s teams, customers and ecosystem. Our goal is to create tools that are user-friendly and reliable, ensuring that Atlassian teams can easily embrace and utilize them. These tools will facilitate the development, deployment, measurement, and operation of AI & ML experiences. They will seamlessly integrate with the Atlassian Data Platform, enabling teams to efficiently and rapidly incorporate AI & ML capabilities into their workflows. The focus is on providing a smooth and hassle-free experience for Atlassian users, allowing them to leverage the power of AI & ML without any complications.

Responsibilities:

Job description:

As a Principal Engineer on the AI & ML Platform team, you will build and shape the core infrastructure to allow software engineers, ML engineers & data scientists to develop, train, evaluate, deploy, and operate Machine Learning models and pipelines. Along with that, you will build systems for product teams like Jira & Confluence to provide access to curated LLMs. You will use your software development expertise to solve difficult problems, tackling complex infrastructure and architecture challenges.

You will have the opportunity to lead engineers to drive involved projects from technical design to launch. You will also collaborate with other teams and internal customers to set expectations, gather input and communicate results.

In This Role, You’ll Get The Chance To:

• Regularly tackle the largest and most complex problems in the team, from technical design to launch.
• Deliver solutions that are used by other teams and products.
• Routinely tackle complex architecture challenges and defines architectural standards.
• Lead code reviews & documentation as well as take on complex bug fixes, especially on high-risk problems.
• Partner across engineering teams to take on company-wide initiatives spanning multiple projects.
• Mentor junior members on the team.

Our tech stack is primarily Java/Kotlin built on AWS.

Qualifications:

On your first day, we’ll expect you to have:

• Fluency in at least one modern object-oriented programming language (preferably Java/Kotlin and Python).
• Understanding of Machine Learning project lifecycle and tools.
• Experience in architecting and implementing high-performance RESTful microservices.
• Experience building and operating large scale distributed systems using Amazon Web Services (S3, Kinesis, Cloud Formation, EKS, AWS Security and Networking).
• Experience with Continuous Delivery and Continuous Integration.

It would be great, but not required if you have:

• Expert-level SQL knowledge, query tuning, schema design, and ETL processes.
• Experience with Databricks or Apache Spark.
• Experience with Amazon Sagemaker.
• Experience with scaling and deploying Machine Learning models.
• Experience with using LLMs.