Senior AI Engineer

NovoEd; Canada; On-site; CAD 120,000 - 160,000; Full time

Benefits offered by this job

Benefits Package with time off and HOL

Job summary

You should have 3–5+ years of backend experience in Python, familiarity with LLM integration and prompt engineering, and a strong focus on testing and reliability. This role offers autonomy in a fast-moving team and opportunities to shape our AI stack.

Qualifications

• 3–5+ years professional backend engineering experience in Python, FastAPI or Flask, and background processing.
• Masters Degree in related field.
• Proven record of deploying Python applications to production (not just scripts or academic work).
• Strong grasp of software design patterns.
• Strong understanding of backend performance, parallel processing in background jobs and multi-threading.
• Proficiency in performance tuning especially for heavy AI models.
• Applied machine learning experience — training, evaluating, and maintaining small task-specific models.
• Familiarity with LLM integration, prompt engineering, and context window optimization.
• Proven ability to debug AI behavior, identify root causes, and make targeted fixes.
• Strong testing discipline for both backend and AI components.
• Experience with background processing with Celery or other major libraries.
• Experience with monitoring APIs and background processing.
• Experience with ensuring visibility and error reporting.
• Nice to have: experience with Docker, understanding of CI/D, deployment automation and Kubernetes

Responsibilities

• Design, develop, and deploy production-grade AI-powered backend systems.
• Integrate LLMs and traditional ML models into scalable architectures.
• Integrate and optimize vector databases for retrieval-augmented generation (RAG) pipelines and other ML queries.
• Write clean, well-structured Python code following best practices.
• Consider performance and latency in system design to ensure fast decision making.
• Build hybrid architectures balancing LLM calls with traditional ML.
• Debug complex issues across backend, AI inference, and UI integration.
• Conduct thorough dev testing before QA handoff to ensure production reliability.
• Collaborate with product, backend, and frontend engineers to deliver cohesive solutions.

Skills

Python

FastAPI/Flask

Background processing

LLM integration

Prompt engineering

Context window optimization

Debug AI behavior

Testing discipline

Performance tuning for AI models

Distributed systems

Education

Masters Degree in related field

Tools

Celery

Docker

Kubernetes

CI/CD

FastAPI

Job description

About Us

We're a fast-growing product company integrating cutting-edge AI capabilities into our core offering to stay competitive and deliver exceptional value to customers. Our AI work spans task-specific ML models, large language model (LLM) integration, and agentic systems that orchestrate multiple tools to produce end-user results.

About Us

We're a fast-growing product company integrating cutting-edge AI capabilities into our core offering to stay competitive and deliver exceptional value to customers. Our AI work spans task-specific ML models, large language model (LLM) integration, and agentic systems that orchestrate multiple tools to produce end-user results.

What You'll Do

• Design, develop, and deploy production-grade AI-powered backend systems.
• Integrate LLMs and traditional ML models into performant, scalable architectures.
• Integrate and optimize vector databases for retrieval-augmented generation (RAG) pipelines and other traditional ML queries.
• Write clean, well-structured, and testable Python code following best practices.
• Capable of thinking about performance and ensuring optimal decision making to reduce latency.
• Build hybrid architectures that balance LLM calls with traditional ML.
• Debug complex, cross-layer issues spanning backend, AI inference, and UI integration.
• Conduct thorough dev testing before QA handoff to ensure production reliability.
• Collaborate with product, backend, and frontend engineers to deliver cohesive solutions.

Must-Have Skills & Experience

• 3–5+ years professional backend engineering experience in Python, FastAPI or Flask, and background processing.
• Masters Degree in related field
• Proven record of deploying Python applications to production (not just scripts or academic work).
• Strong grasp of software design patterns
• Strong understanding of backend performance, parallel processing in background jobs and multi-threading
• Proficiency in performance tuning specially for heavy AI models
• Applied machine learning experience — training, evaluating, and maintaining small task-specific models.
• Familiarity with LLM integration, prompt engineering, and context window optimization.
• Proven ability to debug AI behavior, identify root causes, and make targeted fixes.
• Strong testing discipline for both backend and AI components.
• Experience with background processing with Celery or other major libraries
• Experience with monitoring APIs and background processing
• Experience with ensuring visibility and error reporting.
• Nice to have: experience with Docker, understanding of CI/D, deployment automation and Kubernetes

Who Will Succeed in This Role

• Independent problem solver — you can debug without constant supervision.
• Production mindset — you understand that reliability, scalability, and maintainability matter as much as accuracy.
• System thinker — you see backend, AI, and UI as a connected whole.

Why Join Us

• Direct impact on the company's competitive edge.
• Small, fast-moving team with high autonomy.
• Work on practical, real-world AI applications — not just research.
• Opportunity to shape our AI architecture and best practices from the ground up.
• Benefits Package, with time off and Holiday pay

If you're a backend-first AI engineer who thrives in shipping production-ready systems and knows how to make AI practical, fast, and reliable — we'd love to talk.