Jobgether
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. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1