Senior AI Engineer

NovoEd

. Design, develop, and deploy production-grade AI-powered backend systems .

Posted 11/4/2026full-timeRemote • CanadaSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and deploying AI-powered backend systems using Python, with a strong focus on performance optimization and integration of machine learning models. Proven ability to collaborate effectively with cross-functional teams to deliver reliable and scalable solutions.

Highest-signal resume keywords

Python DevelopmentFastAPI or FlaskPerformance Tuning for AI ModelsMachine Learning IntegrationBackground Processing with Celery

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Backend EngineeringSoftware Design PatternsParallel ProcessingMulti-threadingDebugging AI BehaviorTesting DisciplineDeployment AutomationContext Window OptimizationRetrieval-Augmented Generation (RAG)Performance Optimization

Soft Skills

CollaborationProblem Solving

Tools & Technologies

CeleryDockerKubernetesCI/CDMonitoring APIs

Certifications & Qualifications

Masters Degree in Related Field

Industry Keywords

AI-Powered SystemsMachine LearningVector DatabasesProduction ReliabilityBackground Processing

Tech Stack

Tools & technologies

DockerFlaskKubernetesPython

About the role

Key responsibilities & impact

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
Think about performance and ensure 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

Requirements

What you’ll need

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
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

Benefits

Comp & perks

Benefits Package, with time off and Holiday pay
Direct impact on the company’s competitive edge
Small, fast-moving team with high autonomy
Opportunity to shape AI architecture and best practices from the ground up