AI Infrastructure Engineer

About the role

We're looking for Senior+ AI Infrastructure Engineers to build the systems that train and serve Intercom's next generation of AI products. You'll join a small, highly technical team working at the cutting edge of modern AI infrastructure, building training pipelines and running inference for custom models like Fin Apex.

What you'll do

• Implement and scale training pipelines for large transformer and LLM models, from data ingestion and preprocessing through distributed training and evaluation.
• Build and optimize inference services that deliver low-latency, high-reliability experiences for our customers, including autoscaling, routing, and fallbacks.
• Work on GPU-level performance: tuning kernels, improving utilization, and identifying bottlenecks across our training and inference stack.
• Collaborate closely with ML scientists to implement cutting edge training and inference methods and bring them to production.
• Play an active role in hiring, mentoring, and developing other engineers on the team.
• Raise the bar for technical standards, reliability, and operational excellence across Intercom's AI platform.

What you'll need

• 5+ years of experience in software engineering, with a strong track record of shipping high-quality products or platforms.
• Degree in Computer Science, Computer Engineering, or a related field (or equivalent experience with very strong fundamentals).
• Hands-on experience with model training (especially transformers and LLMs), model inference at scale, or low-level GPU work such as writing CUDA or Triton kernels.
• Comfortable working in production environments at meaningful scale (traffic, data, or organizational).
• Deep knowledge of at least one programming language; ability to write clean, reliable code and learn new stacks quickly.
• Communicates clearly and enjoys close collaboration with both engineers and non-engineers.

Nice to have

• Experience at AI native companies that train and/or run inference for their own models.
• Experience running training or inference workloads on Kubernetes.
• Experience with AWS or other major cloud providers.
• Production experience with Python in ML or infrastructure contexts.

What they offer

• Competitive salary, annual bonus and equity
• Unlimited access to Claude Code and best-in-class AI tools
• Generous paid time off above statutory minimum
• Hybrid working (minimum three days per week in office)