Senior LLMOps Engineer -Cloud / AI Infrastructure

Location:

Downtown Toronto Hybrid:

4 days in office

Ready to build what powers the next generation of AI?

We’re looking for a

Staff LLMOps Engineer

to lead the design, deployment, and optimization of

large language model (LLM)

infrastructure on the cloud. You’ll be the driving force behind taking trained models from lab to production—scaling efficiently across multi-GPU clusters and pushing the boundaries of

inference performance

for enterprise-grade AI applications.

If you thrive at the intersection of

AI, cloud engineering, and systems optimization , this is your chance to shape the future of large-scale model serving in a high-impact environment.

What You’ll Do Architect and operationalize

LLM deployment pipelines

on AWS and Kubernetes/EKS.

Build and scale

multi-GPU inference infrastructure

for low latency, high availability, and cost efficiency.

Optimize inference using frameworks like

vLLM, SGLang, and DeepSpeed-Inference .

Implement advanced serving techniques: continuous batching, speculative decoding, KV-cache management, and distributed scheduling.

Collaborate with AI researchers to convert model training outputs into

production-grade APIs and services .

Establish

observability and monitoring

for latency, throughput, GPU utilization, and failure recovery.

Automate provisioning, scaling, and upgrades using

Terraform and CI/CD pipelines .

Ensure compliance, security, and efficiency in multi-tenant LLM hosting for enterprise clients.

What We’re Looking For 6+ years

in DevOps, ML infrastructure, or cloud platform engineering.

2+ years

of direct experience deploying and optimizing LLMs or large-scale ML models.

Expertise with

GPU-accelerated inference

and distributed serving environments.

Deep familiarity with

cloud-native architectures (AWS, GCP, Azure)

and

Kubernetes .

Strong foundation in

Python, Bash, and IaC (Terraform) .

Experience integrating

monitoring tools

(Prometheus, Grafana, Datadog) for performance visibility.

Passion for building robust, scalable, and secure AI systems.

Why Join Lead and

own mission-critical AI infrastructure

at a fast-scaling startup.

Work alongside world-class engineers, data scientists, and innovators.

Competitive salary +

meaningful equity

in a company redefining applied AI.

A culture built on innovation, technical depth, and impact—your work truly matters.

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