Senior Agentic AI Engineer

Location: Toronto, ON

Work Arrangement: Hybrid – 50% Remote

Employment Type: Long term contract

Interview: 3 rounds

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We are seeking a Senior Agentic AI Engineer to design, develop, and deploy production-grade AI applications using Large Language Models (LLMs), Agentic AI frameworks, Retrieval-Augmented Generation (RAG), and Google Cloud Platform (GCP).

The ideal candidate will have strong Python development skills, hands-on experience building agentic AI solutions, and the ability to troubleshoot complex RAG pipelines, evaluate LLM application quality, and design scalable cloud-based architectures. This role requires solid software engineering fundamentals and the ability to take AI solutions from design and development through deployment, monitoring, and continuous improvement.

Key Responsibilities:

- Design, develop, and maintain agentic AI applications and LLM-powered solutions for enterprise use cases.
- Build and orchestrate multi-step AI workflows using LangGraph, LangChain, or similar frameworks.
- Develop RAG pipelines using embeddings, vector search, and retrieval optimization techniques to deliver accurate, relevant, and grounded responses.
- Troubleshoot RAG performance issues across document ingestion, chunking, embeddings, retrieval, reranking, context construction, and response generation.
- Design and implement evaluation strategies for LLM and agentic AI applications, including retrieval quality, answer relevance, groundedness, hallucination detection, and regression testing.
- Implement LLM observability, tracing, monitoring, and troubleshooting using Langfuse or comparable platforms.
- Develop and integrate MCP-based tools and services to connect AI agents with enterprise systems, APIs, and data sources.
- Build RESTful APIs and backend services using Python frameworks such as FastAPI or Flask.
- Leverage Google Cloud services, particularly Vertex AI and BigQuery, to build and integrate cloud-based AI solutions.
- Implement prompt engineering, tool calling, structured outputs, context management, and appropriate human-in-the-loop controls.
- Apply software engineering best practices, including automated testing, version control, CI/CD, and production deployment.
- Implement security, data privacy, responsible AI, and governance controls appropriate for enterprise AI applications.
- Collaborate with product managers, architects, data engineers, and other stakeholders in an Agile delivery environment.
- Troubleshoot production issues and continuously improve application reliability, performance, scalability, and response quality.

Required Skills and Experience:

- 5+ years of qualified software development experience.
- 2+ years of hands-on experience developing agentic AI or LLM-powered applications.
- Strong Python programming and software engineering fundamentals.
- Demonstrated experience building, deploying, and supporting LLM-powered applications.
- Hands-on experience with LangGraph, LangChain, or a similar AI application framework.
- Experience with Langfuse or another LLM observability platform.
- Understanding of Model Context Protocol (MCP) and its use in connecting AI agents with tools and enterprise systems.
- Hands-on experience with Google Cloud services, particularly Vertex AI and BigQuery, with the ability to explain architecture decisions and service integrations.
- Experience developing RAG solutions using embeddings and vector search.
- Strong understanding of RAG troubleshooting, retrieval optimization, and techniques for improving answer quality and grounding.
- Experience evaluating LLM and agentic AI applications using measurable metrics, test datasets, and regression testing.
- Experience developing RESTful APIs using FastAPI, Flask, or a similar framework.
- Understanding of prompt engineering, tool calling, structured outputs, context management, and multi-step agent workflows.
- Experience with automated testing, Git, CI/CD, and production deployment practices.
- Understanding of data privacy, AI safety, responsible AI principles, and enterprise application security.
- Experience working with Agile methodologies.
- Excellent verbal and written communication skills, including the ability to explain technical designs, troubleshooting approaches, and engineering trade-offs.

📌 Senior Agentic AI Engineer (Toronto)
🏢 EnableIT
📍 Toronto