Senior Cloud Platform Engineer (AWS), AI Infrastructure - Evinova

Role overview

Workplace

• The role follows a hybrid model, with employees expected to work from the office three days per week.
• The role is in the Greater Toronto Area; candidates must live within commuting distance or be willing to relocate.

Cloud platform engineering

• Build and operate scalable AWS platforms and reusable infrastructure, tooling, deployment patterns, and self-service capabilities.
• Write and maintain AWS infrastructure as code, primarily CDK in TypeScript and/or Python; create reusable CDK constructs.
• Operate containerized workloads on Amazon ECS and AgentCore; build capabilities for compute, networking, IAM, secrets, storage, model access, and isolation.
• Build CI/CD and GitOps workflows and help move prototypes and research workloads into production-grade services.

Reliability and operations

• Improve availability, scalability, resilience, and performance; implement autoscaling, load balancing, retries, fallback, rate limiting, and recovery strategies.
• Establish monitoring, alerting, SLOs, runbooks, and production-readiness standards; troubleshoot production issues across infrastructure, containers, applications, and model providers.
• Automate operations and optimize cloud and model costs through capacity management and data-driven analysis.

AI gateway and observability

• Build a centralized AI gateway that routes requests across model providers and supports secure, governed access, fallback, authentication, quotas, and cost controls.
• Support production agentic AI, RAG, and conversational AI infrastructure; enable teams to change model providers without tightly coupling applications to endpoints.
• Build GenAI observability for token use, latency, throughput, errors, provider performance, and cost attribution; integrate tools such as CloudWatch, OpenTelemetry, Datadog, and Splunk.
• Build telemetry pipelines and security, auditability, and governance controls for regulated AI workloads; support applicable GCP, GMLP, and GxP practices.

Essential experience

• At least 4 years in platform engineering, infrastructure, SRE, or DevOps, with infrastructure code as the main output.
• Deep hands-on AWS production cloud engineering; experience with AWS services such as Bedrock, ECS, IAM, VPC, load balancing, S3, CloudWatch, and Secrets Manager.
• Strong IaC experience. AWS CDK in Python and/or TypeScript is preferred; Terraform engineers willing to work in CDK are welcome.
• Strong Docker and Amazon ECS experience, including deployment, autoscaling, resource management, health checks, networking, security, and troubleshooting.
• Experience with production CI/CD and/or GitOps; on-call, incident response, and root-cause analysis.
• Strong Python and/or TypeScript skills and experience building production platform tooling and automation.
• Experience with production observability tools and partnering with software, data, or ML/AI teams to move workloads into production.
• Strong understanding of reliability, scalability, observability, performance, security, and cost optimization; strong written and verbal communication.

Preferred experience

• Preferred: internal developer platforms, production generative AI/LLM workloads, enterprise model platforms, AI gateways, model routing, and provider abstraction.
• Preferred: agentic AI, multi-agent systems, RAG, conversational AI, AgentCore, Model Context Protocol, or LLM evaluation and observability platforms.
• Preferred: regulated-industry ML/AI infrastructure, GxP controls, and Kubernetes/Amazon EKS, including migrations to ECS.

Working approach

• The role calls for reusable-platform thinking, operational focus, hands-on delivery, and attention to developer experience.
• The successful candidate collaborates across engineering, security, infrastructure, and product teams; manages competing priorities; and works autonomously in an evolving environment.

Compensation

• Annual base salary is 134,855.20–176,997.45; permanent positions may include annual variable pay and long-term incentives.
• The posting also discusses benefits for permanent and fixed-term roles; the structured employment type is temporary.