About this role
Accountabilities
- Contribute to architectural design across cloud infrastructure, data platforms, and AI/ML systems, taking ownership of significant technical components.
- Build and integrate cloud-native solutions involving microservices, serverless applications, containers, and event-driven workloads across platforms such as AWS, Azure, and GCP.
- Implement infrastructure-as-code and automated CI/CD pipelines using technologies such as Terraform, CloudFormation, and GitHub Actions.
- Design and contribute to data architectures, including data pipelines, warehouses, modeling, and ETL/ELT workflows using tools such as Snowflake, BigQuery, Airflow, and dbt.
- Support the design and implementation of AI/ML systems, including model serving, MLOps pipelines, and LLM-based capabilities.
- Implement monitoring, logging, and observability solutions using platforms such as Prometheus, Grafana, and CloudWatch.
- Apply modern AI-assisted development tools such as Claude, Cursor, and similar technologies to improve development speed and quality.
- Collaborate with engineering, data, AI, and product teams to translate business and technical requirements into practical solutions.
- Communicate architectural tradeoffs and technical decisions clearly to both technical and cross-functional stakeholders.
- Maintain architecture and technical documentation that supports reproducibility, onboarding, and shared team understanding.
- Participate actively in technical design reviews, raising potential risks and providing constructive feedback.
- Take increasing end-to-end ownership of system components and progressively larger areas of architectural responsibility.
- Contribute to technical standards, patterns, and best practices that improve engineering quality and consistency.
- Begin mentoring junior engineers by sharing technical knowledge, guidance, and practical experience.
Requirements
- 5+ years of professional software engineering experience , including exposure to architectural decision-making and system design.
- Working knowledge of major cloud platforms and cloud-native architectures, including AWS, Azure, or GCP.
- Strong proficiency in Python and at least one additional modern programming language such as Java, Scala, or TypeScript.
- Hands-on experience with containerization and orchestration technologies such as Docker and Kubernetes.
- Practical experience with infrastructure as code and CI/CD tools including Terraform, CloudFormation, and GitHub Actions.
- Working knowledge of relational and NoSQL databases, along with data pipelines and ETL/ELT concepts, using technologies such as PostgreSQL, MongoDB, Airflow, or dbt.
- Familiarity with AI/ML system design, including model deployment, MLOps, and LLM integration using tools such as SageMaker, Vertex AI, MLflow, or Hugging Face.
- Understanding of microservices, serverless, and event-driven architecture patterns.
- Awareness of cloud security, compliance, observability, and governance fundamentals, including frameworks such as GDPR, HIPAA, and SOC 2.
- Experience with OpenSearch or Elasticsearch operations and migration, OpenSearch Dashboards, security controls such as FGAC/DLS/FLS, or related search and observability technologies is valuable.
- Strong analytical and problem-solving abilities, with the ability to navigate ambiguous and evolving technical challenges.
- Demonstrable experience using AI-assisted development tools such as Claude and Cursor.
- Strong communication and collaboration skills, with a willingness to give and receive direct, constructive feedback.
- A proactive, ownership-oriented approach and the ability to work effectively in fast-moving environments.
- Curiosity and adaptability, with an interest in continuously developing technical expertise as cloud and AI technologies evolve.
- Must be legally authorized to work in Canada or the US, with applications from outside these locations not considered.
Benefits
- $53–$73 USD per hour , with compensation determined based on factors such as experience, qualifications, skills, seniority, geographic location, and business needs.
- Opportunities for a fully remote working arrangement within Canada or the US.
- Comprehensive benefits package for eligible employees.
- Paid time off .
- Medical, dental, and vision insurance .
- 401(k) benefits for eligible employees.
- Opportunity to work on complex, production-focused cloud, data, and AI/ML initiatives.
- Exposure to modern cloud-native technologies, AI systems, infrastructure automation, and AI-assisted development practices.
- Collaboration with experienced technical professionals and cross-functional teams.
- Opportunities to expand architectural ownership, mentor other engineers, and influence technical standards.
- A culture emphasizing craftsmanship, continuous learning, direct communication, ownership, and practical delivery.
- Equal employment opportunities and consideration based on job-related qualifications, regardless of legally protected characteristics.
- Background checks may be required in accordance with applicable local legislation, with current employers 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.
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