Staff Cloud Architect (L4) — Multi-Cloud AI/ML

RemoteLeads

United States

Remote

USD 55,000 - 83,000

Full time

3 days ago

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Benefits offered by this job

CAD $53–$74 per hour

Six-month contract

Paid time off

Medical, dental, and vision insurance

Job summary

RemoteLeads is seeking a Senior Cloud Architect to define strategy across cloud, data, and AI/ML systems in a high-scale environment. You will design multi-cloud, hybrid solutions and lead data warehousing, pipelines, and ML model serving with modern tooling.

You will mentor engineers, drive DevOps, security, and governance standards, and collaborate with clients and product teams to shape technical direction and architecture roadmaps. Strong leadership and cloud expertise are essential.

Qualifications

8+ years of software engineering experience, including architecture/leadership.
Deep expertise in AWS, Azure, GCP or comparable cloud platforms.
Experience with microservices, serverless, containers, 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 with relational, NoSQL, and big data systems.
Hands-on data modeling, ETL/ELT, and orchestration tools such as Airflow, Prefect, and dbt.
Experience designing production AI/ML systems, including LLMs, MLOps, and model serving.
Understanding of cloud networking, security, IAM, governance, compliance, and observability.
Strong Python, API, and containerization skills; mentoring and stakeholder communication.
Certifications in TOGAF/AWS/Azure/GCP preferred.

Responsibilities

Define technical strategy and architecture across cloud, data, and AI/ML systems.
Design scalable cloud-native, multi-cloud, and hybrid solutions.
Architect data warehouses, lakes, pipelines, and batch or streaming workloads.
Design production AI/ML systems, including model serving, MLOps, feature stores, and LLM apps.
Establish infrastructure-as-code, CI/CD, DevOps, security, governance, and compliance standards.
Optimize deployed systems for performance, scalability, cost, and reliability.
Lead cloud migrations and platform modernization initiatives.
Partner with clients, leadership, engineering, data, AI, and product teams on technical direction.
Maintain architecture documentation, standards, and guidelines.
Mentor engineers, resolve complex escalations, and evaluate emerging technologies.