This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sr. AI Engineer based in Canada.
This role offers the opportunity to build and scale advanced AI-powered systems that create meaningful customer value.
The successful candidate will combine strong backend engineering expertise with applied AI skills to deliver reliable, production-ready solutions.
You will work on integrating large language models, machine learning models, and intelligent workflows into scalable architectures.
The position focuses on solving complex engineering challenges across AI infrastructure, backend performance, and user-facing applications.
You will collaborate with cross-functional teams while helping shape AI architecture, best practices, and future capabilities.
This is an ideal opportunity for an experienced engineer who enjoys moving beyond experimentation to build practical AI solutions that operate at scale.
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sr. AI Engineer based in Canada.
This role offers the opportunity to build and scale advanced AI-powered systems that create meaningful customer value.
The successful candidate will combine strong backend engineering expertise with applied AI skills to deliver reliable, production-ready solutions.
You will work on integrating large language models, machine learning models, and intelligent workflows into scalable architectures.
The position focuses on solving complex engineering challenges across AI infrastructure, backend performance, and user-facing applications.
You will collaborate with cross-functional teams while helping shape AI architecture, best practices, and future capabilities.
This is an ideal opportunity for an experienced engineer who enjoys moving beyond experimentation to build practical AI solutions that operate at scale.
Accountabilities
- Design, develop, and deploy production-grade AI-powered backend systems that are scalable, reliable, and maintainable.
- Integrate large language models (LLMs), machine learning models, and AI-driven workflows into existing product architectures.
- Build and optimize retrieval-augmented generation (RAG) pipelines using vector databases and other machine learning approaches.
- Develop clean, structured, and testable Python code following software engineering best practices.
- Design hybrid AI architectures that balance traditional machine learning approaches with LLM capabilities to optimize performance and reliability.
- Improve system performance by reducing latency, optimizing AI model execution, and making efficient architectural decisions.
- Debug complex issues across backend services, AI inference workflows, and application integrations.
- Implement strong testing practices for backend systems and AI components to ensure production quality.
- Collaborate with product, backend, and frontend engineering teams to deliver cohesive AI-powered features.
- Monitor APIs and background processing systems, improve observability, and ensure effective error reporting.
- Contribute to deployment automation, infrastructure improvements, and engineering best practices where applicable.
- 3–5+ years of professional backend engineering experience with Python and frameworks such as FastAPI or Flask.
- Proven experience deploying Python applications into production environments, beyond scripts, prototypes, or academic projects.
- Strong understanding of software design patterns, backend architecture, and scalable system development.
- Solid knowledge of performance optimization, parallel processing, background jobs, and multi-threading concepts.
- Experience optimizing systems that rely on complex or resource-intensive AI models.
- Practical machine learning experience, including training, evaluating, and maintaining task-specific models.
- Familiarity with LLM integration, prompt engineering, context optimization, and AI behavior troubleshooting.
- Ability to analyze AI outputs, identify root causes of issues, and implement targeted improvements.
- Experience with background processing frameworks such as Celery or similar technologies.
- Strong testing discipline and commitment to building reliable production systems.
- Experience with monitoring, observability, and error tracking for APIs and asynchronous workflows.
- Knowledge of Docker, CI/CD practices, deployment automation, and Kubernetes is considered an asset.
- Strong problem-solving skills with the ability to work independently and manage complex technical challenges.
- A systems-oriented mindset with the ability to understand how backend, AI, and user-facing components work together.
- Opportunity to directly influence the development of practical, real-world AI solutions.
- High-autonomy environment within a fast-moving technology team.
- Ability to shape AI architecture, engineering standards, and best practices from the ground up.
- Remote work flexibility while contributing to impactful AI-driven products.
- Opportunity to work on production AI systems rather than purely experimental research projects.
- Collaborative environment with close partnership across product, backend, and frontend teams.
- Competitive compensation package based on experience and expertise.