Staff Cloud Architect L4

Accountabilities

• Define technical strategy and lead end-to-end architectural design across cloud infrastructure, data platforms, and AI/ML systems.

• Design scalable cloud-native architectures, including multi-cloud and hybrid environments using platforms such as AWS, Azure, GCP, and Kubernetes.

• Develop data architectures covering warehouses, data lakes, batch and streaming pipelines, and modern data platforms.

• Architect production AI/ML solutions, including model-serving infrastructure, MLOps pipelines, feature stores, and LLM-based applications.

• Establish infrastructure-as-code, CI/CD, and DevOps standards using technologies such as Terraform, CloudFormation, Pulumi, and GitHub Actions.

• Lead initiatives focused on performance, scalability, reliability, security, governance, and cloud cost optimization.

• Drive cloud migrations and platform modernization initiatives from architectural planning through delivery.

• Ensure solutions align with relevant security, compliance, governance, and observability requirements, including frameworks such as GDPR, HIPAA, and SOC 2.

• Partner with technical and business leadership to translate organizational goals into practical architectural decisions.

• Communicate complex technical concepts clearly to engineering, product, data, AI, and non-technical stakeholders.

• Develop and maintain architecture documentation, standards, patterns, and technical guidelines.

• Establish engineering and architecture best practices that improve quality and consistency across teams.

• Mentor junior and mid-level engineers and help strengthen their technical and architectural capabilities.

• Serve as a senior escalation point for complex architectural, integration, and technical challenges.

• Evaluate emerging technologies and recommend tools, frameworks, and patterns that can improve technical outcomes.

• Incorporate modern AI-assisted development tools into day-to-day engineering workflows to improve productivity and quality.

Requirements

• 8+ years of software engineering experience, including at least 3 years in architecture or technical leadership roles.

• Deep expertise in cloud platforms and cloud-native architecture, particularly AWS, Azure, or GCP.

• Strong experience with microservices, serverless architectures, containers, and event-driven systems, including technologies such as Kubernetes, Docker, Lambda, and EventBridge.

• Proficiency with infrastructure as code and CI/CD tools such as Terraform, CloudFormation, Pulumi, and GitHub Actions.

• Strong data architecture experience across relational, NoSQL, and large-scale data systems, including technologies such as PostgreSQL, MongoDB, Snowflake, BigQuery, Spark, and Kafka.

• Hands-on experience with data modeling, ETL/ELT pipelines, and orchestration platforms such as Airflow, Prefect, or dbt.

• Proven experience designing and delivering production AI/ML systems, including LLM applications, MLOps, and model serving, with technologies such as SageMaker, Vertex AI, MLflow, Hugging Face, PyTorch, or TensorFlow.

• Solid understanding of cloud networking, security, identity, access management, governance, compliance, and observability.

• Strong software engineering capabilities, including Python, API development, and containerization.

• Demonstrated experience providing technical leadership and mentoring engineers.

• Strong communication and stakeholder-management skills, with the ability to translate technical concepts for audiences with different levels of expertise.

• Demonstrable experience using AI-assisted development tools such as Claude, Cursor, or comparable platforms.

• Ability to work with ownership, sound judgment, adaptability, and a strong focus on delivery and technical quality.

• Comfortable working in fast-changing environments where requirements, technologies, and constraints can evolve quickly.

• Experience with multi-cloud architecture, responsible AI or AI ethics, or enterprise architecture certifications such as TOGAF or AWS/Azure/GCP certifications is considered an asset.

• Must be legally authorized to work in Canada or the United States; applications from outside Canada and the US are not considered for this opportunity.

• Willingness to complete applicable identity verification and background-check requirements as part of the hiring process.

Benefits

• $53–$74 CAD per hour, depending on factors such as experience, qualifications, skills, seniority, location, and business requirements.

• 6-month contract with potential for extension.

• Fully remote work within Canada or the US.

• Opportunity to work on complex cloud, data, and AI/ML initiatives with highly experienced technical teams.

• Exposure to modern technologies and production AI systems, including LLMs, MLOps, cloud-native infrastructure, and AI-assisted development.

• Comprehensive benefits package for eligible employees, including paid time off and medical, dental, and vision insurance.

• 401(k) benefits for eligible employees.

• Opportunities to provide technical mentorship and influence architectural standards across major engagements.

• Work alongside experienced professionals and contribute to production systems designed for real-world enterprise environments.

• Equal employment opportunity and reasonable consideration for qualified applicants regardless of legally protected characteristics.

• Background checks, where applicable, are conducted in accordance with local legislation, and current employers are not contacted without permission.