AI Platform Engineer

Summary:

• Duration: 12 Months Contract
• Work Mode: Hybrid (Day 1 onboarding onsite / in office presence 3x week)
• 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.
• Hands-on 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.