Cloud Architect - AI/ML for Developer Productivity (Multi-Cloud)
Cloud Architect Aversan Inc. (www.aversan.com) is a trusted multi-service engineering and electronics manufacturing company. Aversan delivers leading-edge and reliable safety-critical electronics and software systems to the aerospace, defence, and space industries. We at Aversan are embarking on an exciting initiative to build a next-generation cloud platform from the ground up for our client -engineered to support mission-critical SaaS solutions such as connected vehicles across AWS, GCP, Azure, and on-premise environments. As part of this initiative, we're exploring collaboration across business units, leveraging existing Large Language Model (LLM) capabilities to strengthen and speed up our AI integration strategy. We're seeking a hands-on Cloud Architect to lead this effort-someone who can design and deliver intelligent, self-optimizing systems and developer experiences powered by generative AI, predictive analytics, and automation. Location: Canada Job Type: Full Time Working Arrangement: Remote
Responsibilities
Drive AI-Powered Developer Productivity: Architect and implement intelligent workflows across coding, testing, deployment, and debugging by integrating LLMs (e.g., GPT, Claude, CodeLlama) into code editors, CI/CD pipelines, and developer tools for smart code generation, bug detection, and automated PR reviews. Architect Intelligent CI/CD & Observability Systems: Design scalable multi-cloud CI/CD pipelines (ArgoCD, Jenkins, Tekton) infused with AI for predictive canary analysis, automated rollbacks, and zero-downtime deployments-enhanced by AI-driven log summarization, anomaly detection, and proactive alerting. Embed AI in Security & Compliance: Automate vulnerability detection and remediation with AI classifiers, generate security patches, improve IaC hygiene, and translate compliance standards (TISAX, SOC, FedRAMP, AWS GovCloud) into policy-as-code. Advance AI-Driven Testing & Quality Engineering: Use AI to automate test case generation, simulate load testing patterns, analyze test results, and optimize test coverage for APIs, microservices, and infrastructure components. Develop and Extend Reusable LLM Capabilities: Evaluate, integrate, and fine-tune internal and third-party LLMs to align with Aversan's specific codebases, deployment architectures, and operational needs while defining APIs for reusability across business units. Lead Strategic Collaboration & AI Adoption: Partner with other business units to co-develop and share AI tooling, lead proofs of concept (POCs) and performance benchmarks, and promote AI/ML adoption through training, mentorship, and architectural leadership. Enable Self-Healing and Autonomous Infrastructure: Build intelligent, self-optimizing systems that reduce operational complexity, implement predictive maintenance, and empower platform teams with AI-driven insights for continuous reliability and performance. Basic Qualifications 7+ years of experience in cloud architecture, full-stack development, or platform engineering. 2+ years of hands-on work integrating AI/ML into engineering workflows (e.g., GitHub Copilot, Amazon CodeWhisperer, or custom LLM-based assistants). Proven expertise in: o Cloud platforms: AWS, GCP, and Azure. o AI agent frameworks: Amazon Strands, LangGraph, or similar. o CI/CD pipelines: ArgoCD, Tekton, Jenkins. o Infrastructure-as-code tools: Terraform, Crossplane. o Full-stack technologies: React or Vue.js, Node.js, Python, Java. o Containerized and serverless systems: Kubernetes, EKS, GKE, AWS Lambda, Cloud Run. o Observability and monitoring: Prometheus, OpenTelemetry, Datadog, or ELK stack. Demonstrated ability to build or integrate AI-powered developer platforms or tools that improve engineering productivity.
Nice-to-Have
Qualifications Experience collaborating across teams or business units to share models, services, or infrastructure. Familiarity with MLOps platforms such as MLflow, Kubeflow, or SageMaker Pipelines. Exposure to AI security tools, compliance automation, or FinOps optimization. Professional certifications such as AWS Solutions Architect, GCP Professional Architect, or Certified Kubernetes Administrator (CKA). Please note: Interested applicants must apply directly to this link to be considered for this position: [email protected] The name of the file for the resume should be the applicant's full name and the position title you are applying for. The resume format should be PDF. Apply tot his job Apply To this Job