Staff Engineer - AI/Inference /Gateway

Opportunity

Work Arrangement

• The team operates in a hybrid model combining office collaboration and remote work flexibility.
• New hires are expected to work in the office three days per week.

Role Responsibilities

• Architect and develop scalable, containerized, fault-tolerant Kubernetes services for enterprise AI workloads.
• Build high-performance inference and platform services for Generative AI and Agentic AI applications.
• Optimize distributed systems, storage, networking, and low-level infrastructure components.
• Develop multi-tenant services for on-premises, hybrid, and cloud AI deployments.
• Implement observability architectures using Prometheus, Grafana, Datadog, OpenTelemetry, or similar tools.
• Diagnose production issues and improve reliability, resiliency, and operational efficiency.
• Maintain CI/CD pipelines and deployment automation.
• Implement LLM serving features such as routing, rate limiting, token streaming, load balancing, quotas, and usage budgets.
• Collaborate with globally distributed product, AI, and software engineering teams.
• Participate in the full product lifecycle, from architecture and development through deployment and operations.
• Review code and designs and champion engineering excellence.
• Evaluate emerging technologies and influence the Enterprise AI Platform direction.

Required Qualifications

• At least 8 years of experience developing resilient software products in a product development organization.
• Strong fundamentals in data structures, algorithms, operating systems, networking, and distributed systems.
• Hands-on experience with Docker, Kubernetes, and cloud-native architectures.
• Production backend development experience using Go, Python, C++, or Rust.
• Experience owning CI/CD pipelines and release automation end to end.
• Strong datacenter architecture knowledge covering compute, storage, networking, and virtualization.
• Experience deploying software across on-premises, cloud, and hybrid environments.
• Experience designing and tuning high-performance system software.
• Experience resolving production performance issues with observability and monitoring platforms.
• Familiarity with LLM serving and modern LLM concepts.
• Master's degree in Computer Science or equivalent practical experience.

Preferred Experience

• Experience with PyTorch or TensorFlow, GPU systems, or model-serving platforms such as vLLM, DeepSpeed, Hugging Face TGI, or Triton.
• Experience with RAG, vector databases, AI orchestration frameworks, open-source contributions, production AI platforms, LLM APIs, or agentic systems.
• Experience scaling production LLM APIs with streaming, prompt guardrails, rate limiting, and usage budgeting.

Compensation

• The expected base pay range is CAD $171,000 to CAD $257,000 annually at commencement of employment.
• Total compensation may also include a sign-on bonus, restricted stock units, discretionary awards, and benefits.