Senior Cloud Architect

This is a fully remote position, open to applicants in United States, +1 more country.

📋 Description

• Play a key role in architectural design for cloud, data, and AI/ML systems, taking responsibility for significant components.

• Develop and integrate cloud-native solutions, including microservices, serverless applications, and containerized workloads.

• Execute infrastructure as code and implement CI/CD pipelines.

• Design and contribute to data architectures that encompass pipelines, warehouses, and modeling.

• Assist in the design of AI/ML systems, covering model serving, MLOps pipelines, and the integration of LLM-based functionalities.

• Set up monitoring, logging, and observability for deployed systems.

• Collaborate with engineering, data, AI, and product teams to convert requirements into technical solutions.

• Articulate technical tradeoffs and design choices across various functions.

• Keep architecture documentation up to date.

• Engage in design reviews.

• Assume ownership of system components while increasing architectural responsibilities.

• Contribute to the establishment of architectural standards and best practices.

• Mentor junior engineers and facilitate their professional development.

⛳️ Requirements

• Applications from candidates outside Canada and the US will not be entertained.

• Over 5 years of professional software engineering experience, with insights into architectural decision-making.

• Proficient knowledge of cloud platforms and cloud-native architectures, including AWS, Azure, or GCP.

• Expertise in Python and at least one additional programming language commonly utilized in modern technology stacks, such as Java, Scala, or TypeScript.

• Practical experience with containerization and orchestration tools, such as Docker and Kubernetes.

• Familiarity with infrastructure as code and CI/CD pipelines, including Terraform, CloudFormation, and GitHub Actions.

• Understanding of relational and NoSQL databases, as well as data pipelines and ETL/ELT concepts, such as PostgreSQL, MongoDB, Airflow, and dbt.

• Knowledge of AI/ML system design, including model deployment, MLOps, and LLM integration, utilizing tools like SageMaker, Vertex AI, MLflow, and Hugging Face.

• Comprehension of microservices, serverless, and event-driven architectures.

• Awareness of security, compliance, and observability principles, such as GDPR, HIPAA, and SOC2.

• Proven experience with AI-driven tools like Claude and Cursor.

• Strong problem-solving abilities and the capacity to tackle ambiguous technical challenges.

🏝️ Benefits

• Paid time off

• Medical insurance

• Dental insurance

• Vision insurance

• 401(k)