Genai Engineer

Location –Toronto, ON (Hybrid - 3 days a week onsite)Overall Experience - 7+ yearsAI 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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