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Quantum World Technologies Inc.

GenAI Engineer

Toronto, ON, Canada

Contract

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Job details

Job type: Contract
Apply by: Dec 3, 2026
Posting language: English
Posted: Nov 3, 2026

Original job description

GenAI Engineer

Contract – 6+ months

Location –Toronto, ON (Hybrid - 3 days a week onsite)

Overall Experience - 7+ years

AI Experience - 3+ years

*****Looking explicitly for GenAI development experience. Data Science/ML experience will not counted. ******

Key Responsibilities

Design, develop, and deploy Generative AI applications using LLMs and modern AI frameworks.
Build RAG pipelines using embeddings, vector databases, semantic search, document chunking, and reranking.
Develop LLM-powered workflows using frameworks such as LangChain, LangGraph, LlamaIndex, or Semantic Kernel.
Implement prompt engineering, context management, function calling, and tool integration.
Integrate GenAI solutions with REST APIs, backend services, and enterprise systems.
Evaluate model outputs, improve response quality, and implement measures to reduce hallucinations.
Optimize AI applications for performance, scalability, reliability, and production deployment.

Required Skills

Strong programming experience in Python and API integration.
Hands-on experience with Generative AI, LLMs, and RAG-based applications.
Knowledge of embeddings, vector databases, semantic search, and information retrieval.
Experience with at least one framework: LangChain, LangGraph, LlamaIndex, or Semantic Kernel.
Understanding of prompt engineering, context engineering, and LLM orchestration.
Experience integrating LLMs with backend applications and external tools.
Familiarity with at least one cloud AI platform, such as Azure OpenAI, Amazon Bedrock, or Google Vertex AI.

Preferred Qualifications

Experience developing AI agents or agentic AI workflows.
Knowledge of LLM evaluation, tracing, observability, and hallucination mitigation.
Experience deploying and monitoring GenAI applications in production.
Familiarity with hybrid search, reranking, structured outputs, and inference optimization.

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More about this job

Responsibilities

Design, develop, and deploy Generative AI applications and RAG pipelines using LLMs, modern frameworks, embeddings, vector databases, and search techniques. Integrate LLM workflows with APIs, backend services, and enterprise systems, while evaluating and improving output quality, reducing hallucinations, and optimizing production performance and reliability.

Requirements

Requires 7+ years of overall experience, including 3+ years of hands-on Generative AI development; data science or general machine learning experience does not count toward the AI experience requirement. Candidates need strong Python and API integration skills, practical experience with LLMs and RAG, familiarity with at least one listed LLM framework and cloud AI platform, and knowledge of prompt engineering and orchestration.

Skills

Python
Generative AI
Large Language Models
Retrieval-Augmented Generation
Embeddings
Vector Databases
Semantic Search
LangChain
LangGraph
LlamaIndex
Semantic Kernel
Prompt Engineering
API Integration
LLM Orchestration
Cloud AI Platforms
AI Agents

Visa sponsorship

Not detected in the job text

Keywords

Generative AI
Large Language Models
Retrieval-Augmented Generation
Python
LangChain
LangGraph
LlamaIndex
Semantic Kernel
Embeddings
Vector Databases
Semantic Search
Document Chunking
Reranking
Prompt Engineering
Context Engineering
Function Calling
LLM Orchestration
REST APIs
Azure OpenAI
Amazon Bedrock
Google Vertex AI
AI Agents
LLM Evaluation
Observability
Hallucination Mitigation
Hybrid Search
Structured Outputs
Inference Optimization
Production Deployment
Toronto

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