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Senior AI Engineer Gen AI, LLM, RAG
Job Location:
Monthly Salary:
Experience Required:
Posted:
28 May 2026 (30+ days ago)
Posted:
Application Deadline:
25 August 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Senior AI Engineer
Work Model: Toronto - Hybrid (3 Days/Week Onsite)
Experience Required: 7 Years
Role Overview
We are seeking a Senior AI Engineer to lead the design development and deployment of enterprise-scale Generative AI solutions. This role requires strong expertise in Generative AI full-stack engineering and system architecture with ownership across agentic workflows scalable AI pipelines and high-performance backend systems.
The ideal candidate combines deep technical expertise in LLMs microservices architecture and modern software development practices along with the ability to mentor engineers and drive engineering excellence.
Key Responsibilities
Generative AI Engineering & Architecture
Lead the architecture development and production deployment of enterprise-grade Generative AI systems focused on scalability reliability and performance
Design and implement agentic workflows using LLMs tools and orchestration frameworks to enable intelligent autonomous behavior
Build and integrate end-to-end GenAI pipelines including:
Model inference
Retrieval-Augmented Generation (RAG)
Embeddings
API-based application integration
Collaborate with data and platform teams to implement:
Vector search
Semantic retrieval
Contextual grounding for AI-driven responses
Full-Stack & Backend Engineering:
Develop user-facing GenAI applications alongside robust backend systems
Design and build scalable microservices and secure RESTful APIs for AI/ML capabilities
Integrate Generative AI features with modern front-end technologies
Deployment Operations & Quality:
Lead model deployment packaging and lifecycle management in production environments
Optimize performance and ensure system reliability through:
Test-driven development (TDD)
Reusable component design
Modern architectural principles
Drive CI/CD pipelines containerized deployments and DevOps best practices for AI applications
Collaboration & Leadership:
Provide technical mentorship to engineers and support team development
Participate in and lead architecture design reviews
Champion engineering best practices coding standards and Agile methodologies
Required Skills:
Strong experience in Generative AI and LLM-based system design
Expertise in building scalable microservices and backend systems
Hands-on experience with:
RAG pipelines
Embeddings and vector databases
API-driven AI integrations
Proficiency in full-stack development
Experience with CI/CD DevOps and containerized deployments
Strong understanding of software architecture and distributed systems
Preferred Skills:
Experience with Kubernetes
Exposure to AI & GenAI products and tools
Keywords
Generative AI LLMs Agentic Workflows RAG Microservices Full Stack APIs Kubernetes AI Architecture DevOps
Required Skills:
Experience (Years): 8-10
