AI Platform Engineer

• Design and build a firmwide AI development and evaluation platform with a strong focus on enterprise-scale GenAI benchmarking, assurance, and governance.


• Develop self-service tooling, SDKs, and APIs to enable teams to build, evaluate, and deploy GenAI applications efficiently and safely.


• Build reusable, scalable platform components for GenAI and agentic systems, including orchestration, evaluation pipelines, and model lifecycle workflows.


• Lead the implementation of container-native GenAI workloads on Kubernetes/OpenShift using GitOps-driven deployment patterns.


• Integrate and operate GenAI ecosystem components including LLMs, vector databases, embeddings, and agent frameworks.


• Drive key architecture, product, and design decisions across security, authentication, observability, scalability, and reliability.


• Establish platform best practices for GenAI evaluations, agentic systems, ModelOps/LLMOps, and production operations.


• Collaborate closely with engineers, data scientists, security, and product teams to accelerate safe enterprise adoption of GenAI.

Summary

• Duration: 12 month


• Work Mode: Hybrid


• Location: Montreal

Responsibilities

• Design and build a firmwide AI development and evaluation platform with a strong focus on enterprise-scale GenAI benchmarking, assurance, and governance.


• Develop self-service tooling, SDKs, and APIs to enable teams to build, evaluate, and deploy GenAI applications efficiently and safely.


• Build reusable, scalable platform components for GenAI and agentic systems, including orchestration, evaluation pipelines, and model lifecycle workflows.


• Lead the implementation of container-native GenAI workloads on Kubernetes/OpenShift using GitOps-driven deployment patterns.


• Integrate and operate GenAI ecosystem components including LLMs, vector databases, embeddings, and agent frameworks.


• Drive key architecture, product, and design decisions across security, authentication, observability, scalability, and reliability.


• Establish platform best practices for GenAI evaluations, agentic systems, ModelOps/LLMOps, and production operations.


• Collaborate closely with engineers, data scientists, security, and product teams to accelerate safe enterprise adoption of GenAI.

Requirements

• Minimum 6 years of strong hands-on software engineering experience, preferably in Python (FastAPI, Flask), building large-scale, cloud-native platforms.


• Deep experience designing and operating Kubernetes/OpenShift workloads using Helm, Customize, container registries, and GitOps practices.


• Minimum 3 years of experience building GenAI and LLM-based applications, including agentic orchestration, embeddings, evaluation workflows, and fine-tuning.


• Strong understanding of microservices, RESTful API design, asynchronous and concurrent programming, and performance-oriented systems.


• Solid foundation in data engineering principles including SQL/NoSQL stores, Kafka, Redis, vector databases, and state management at scale.


• Proficiency in DevOps, CI/CD, observability (OpenTelemetry, Prometheus, Grafana), and SRE-inspired operational practices.


• Strong working knowledge of security-first design, OAuth2, secure coding practices, and enterprise-grade platform controls.

Preferred Skills

• Experience with agent-based frameworks or orchestration systems.


• Exposure to LLMOps/ModelOps/evaluation platforms.


• Experience working in enterprise-scale platforms or internal developer platforms.

This role is for an existing vacancy.