GenAI Engineer

Quantum World Technologies Inc.; Toronto; Hybrid; CAD 120,000 - 180,000; Full time

Job summary

Quantum World Technologies Inc. is seeking a senior GenAI developer to design, implement, and deploy Generative AI applications in a hybrid Toronto environment. You will build RAG-based pipelines, embed semantic search, and orchestrate LLM workflows with LangChain, LlamaIndex, or Semantic Kernel.

The role requires 7+ years experience overall and 3+ years in GenAI, with hands-on Python and API integration. Collaboration with backend systems and cloud AI platforms such as Azure OpenAI or Google

Qualifications

• 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 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 Azure OpenAI, Amazon Bedrock, or Google Vertex AI.

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.

Skills

Python

API integration

Generative AI

LLMs

RAG apps

Embeddings

Vector DBs

Semantic search

Prompt engineering

LLM orchestration

LangChain

LangGraph

LlamaIndex

Semantic Kernel

Backend integration

Azure OpenAI

Amazon Bedrock

Google Vertex AI

Job description

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.