AI Engineer
- Toronto, ON, Canada
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Original job description
Senior AI Engineer – Agentic AI / LLM
Location: Toronto, ON
Work Arrangement: Hybrid – 50% Remote
Employment Type: Contract
Interview: 2 rounds
About the Role:
We are seeking experienced Senior AI Engineers to join a leading enterprise technology team and build reliable, production-ready AI agents and LLM-powered applications.
The ideal candidate will have strong hands-on experience developing Agentic AI, LLM applications, RAG solutions, and AI workflows using Python. You will work with technologies including LangGraph, LangChain, Langfuse, Model Context Protocol (MCP), Google Cloud, Vertex AI, and vector search.
You will collaborate closely with product managers, software engineers, architects, and business stakeholders to deliver practical AI solutions for customer service and enterprise operational use cases.
Key Responsibilities:
- Design and develop production-grade LLM-powered applications using Python.
- Build AI agents and multi-step AI workflows using LangGraph, LangChain, or similar frameworks.
- Design and implement Retrieval-Augmented Generation (RAG) solutions using enterprise data, embeddings, and vector search.
- Develop and integrate MCP servers and clients to connect AI agents with enterprise tools, data, and services.
- Implement LLM tracing, monitoring, observability, and evaluation using Langfuse or similar platforms.
- Develop and deploy AI services using Google Cloud, including Vertex AI and BigQuery.
- Build RESTful APIs and integrations supporting AI capabilities.
- Implement prompt engineering, tool calling, structured outputs, context management, and guardrails.
- Develop automated unit and integration tests for AI applications and services.
- Evaluate LLM and agent outputs for accuracy, relevance, reliability, and safety.
- Monitor, troubleshoot, and optimize AI applications in production environments.
- Collaborate with product, engineering, architecture, and business teams in an Agile/Scrum environment.
- Contribute to reusable AI engineering patterns, standards, and best practices.
- Participate in architecture discussions, design reviews, and code reviews.
- Mentor other developers and provide technical guidance.
- Stay current with emerging LLM, Agentic AI, and Generative AI technologies.
Required Qualifications:
- 5+ years of professional software development experience.
- 2+ years of hands-on experience developing Agentic AI or LLM-powered applications.
- Strong proficiency in Python.
- Hands-on experience building and deploying applications using LLMs.
- Experience with LangGraph, LangChain, or a comparable AI application/agent framework.
- Experience building RAG applications using embeddings and vector search.
- Experience with LLM observability, tracing, or monitoring, preferably Langfuse or a comparable platform.
- Understanding of Model Context Protocol (MCP) and how AI agents interact with enterprise tools and services.
- Experience with Google Cloud, preferably Vertex AI and BigQuery.
- Experience developing REST APIs using FastAPI, Flask, or similar frameworks.
- Strong understanding of prompt engineering, tool/function calling, structured outputs, and context management.
- Experience with automated testing, Git, and CI/CD practices.
- Understanding of AI safety, data privacy, responsible AI, and enterprise AI governance.
- Experience working in Agile/Scrum development environments.
- Strong communication and collaboration skills.
More about this job
Responsibilities
Design, build, test, and deploy production-grade LLM applications, AI agents, RAG solutions, and multi-step workflows using Python and cloud services. Monitor and evaluate AI systems, integrate enterprise tools and data, and collaborate with cross-functional teams on architecture, quality, safety, and reusable engineering practices.
Requirements
Requires at least five years of professional software development experience, including two or more years building Agentic AI or LLM-powered applications, with strong Python skills. Candidates should have experience with agent frameworks, RAG and vector search, LLM observability, Google Cloud, REST APIs, automated testing, CI/CD, responsible AI, and Agile/Scrum.
Skills
- Python
- Agentic AI
- Large Language Models
- LangGraph
- LangChain
- Retrieval-Augmented Generation
- Embeddings
- Vector Search
- Model Context Protocol
- Langfuse
- Google Cloud
- Vertex AI
- BigQuery
- REST APIs
- Prompt Engineering
- CI/CD
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Data & Analytics
- Engineering
Keywords
- Python
- Agentic AI
- Large Language Models
- Generative AI
- LangGraph
- LangChain
- Langfuse
- Model Context Protocol
- Google Cloud
- Vertex AI
- BigQuery
- Retrieval-Augmented Generation
- Embeddings
- Vector Search
- REST APIs
- FastAPI
- Flask
- Prompt Engineering
- Tool Calling
- Structured Outputs
- Context Management
- Guardrails
- LLM Observability
- AI Evaluation
- Automated Testing
- Git
- CI/CD
- AI Safety
- Responsible AI
- Agile