AI Software Engineer (Back End)

Job Description

What you would actually do

You will build and maintain the services that sit between the model and the outside world.

This includes work such as:

• Building and maintaining services that handle model inference and user requests
• Designing systems that manage requests, sessions, and streaming responses
• Implementing reliability mechanisms such as rate limiting, retries, and graceful failure
• Building authentication and access controls for public usage
• Designing systems for logging, telemetry, and evaluation signals
• Improving latency, throughput, and reliability of model serving
• Integrating new model checkpoints into the production system
• Working closely with training and infrastructure engineers to deploy and operate the model

Much of the work happens inside production systems: logs, traces, performance profiles, and deployment pipelines. The goal is not polish. The goal is a system that stays up, stays fast, and behaves predictably under load.

The kind of person who does well here

We are looking for engineers early in their careers who want to learn how production AI systems are actually built and operated.

You may have one or two years of experience building production software. What matters most is curiosity, reliability, and the willingness to learn how large scale systems behave under real constraints.

People who tend to do well here:

• Care about runtime behaviour and system reliability
• Enjoy debugging real systems rather than writing theoretical code
• Think clearly about system boundaries and failure modes
• Stay calm and methodical when production behaves unexpectedly
• Want to understand how large scale AI systems actually work

You do not need prior experience serving large language models. You do need the discipline to build systems that are hard to break.

Are you interested in this position?

Apply by clicking on the “Apply Now” button below!

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