As a Principal Engineer on the AI & ML Platform team, you will build and shape the primary infrastructure to allow software engineers, ML engineers and data scientists to train, evaluate 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, solving complex infrastructure and architecture challenges.

You will lead engineers to lead 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.

You'll get the chance to:

• Tackle the largest and most complex problems with the team, from technical design to launch.
• Provide solutions that are used by other teams and products.
• Solve complex architectural challenges and define architectural standards.
• Lead code reviews and documentation and take on complex bug fixes, especially on high-risk problems.
• Partner across engineering teams to take on company-wide programmes.
• Mentor junior members of the team.
• Our tech stack is Java/Kotlin built on AWS.
• 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 architecting and implementing 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.

5+ years of experience with Databricks or Apache Spark.

Experience with Amazon Sagemaker.

5+ years of experience scaling and deploying Machine Learning models.

Experience using LLMs.