Senior AI Engineer

Pacer Staffing; Toronto; On-site; CAD 120,000 - 180,000; Full time

Job summary

Pacer Staffing seeks an experienced software engineer to design and implement AI/LLM-powered applications and agentic workflows. You will build RAG solutions using knowledge graphs, vector search, and embeddings, and develop multi-stage AI agent pipelines with robust state management.

You will also implement prompt engineering, tool calling, and structured outputs, while ensuring observability, CI/CD, and collaboration with engineering and business teams to deliver enterprise AI solutions.

Qualifications

• 6–10 years of software engineering with hands-on production AI/LLM experience.
• Experience with GenAI, LLMs, RAG, and Agentic AI.
• Experience with prompt engineering, structured/JSON outputs, and tool/function calling.
• Experience with knowledge graphs, vector search, and embeddings.
• Experience with Neo4j/Cypher and/or MongoDB Atlas.
• Knowledge of MCP, A2A, or AI agent interfaces.
• Experience with cloud infrastructure, CI/CD, monitoring, and observability.
• Strong Git, code review, and automated testing practices.

Responsibilities

• Design and develop AI/LLM-powered applications and agentic workflows.
• Build RAG and GraphRAG solutions using knowledge graphs, vector search, and embeddings.
• Develop multi-stage AI agent workflows with reliable state management and traceability.
• Build MCP tool servers and A2A interfaces.
• Implement prompt engineering, structured outputs, and tool/function calling.
• Develop AI evaluation frameworks, guardrails, and anti-hallucination controls.
• Build and maintain CI/CD pipelines and production AI infrastructure.
• Implement monitoring, logging, tracing, and observability.
• Collaborate with engineering and business teams to deliver enterprise AI solutions.

Skills

Software engineering

AI/LLM experience

GenAI / LLMs

RAG / Agentic AI

Prompt engineering

Structured JSON outputs

Tool/function calling

Knowledge graphs

Vector search

Embeddings

Neo4j / Cypher

MongoDB Atlas

MCP / A2A interfaces

Cloud infrastructure

CI/CD

Monitoring & observability

Git / code reviews

Automated testing

Tools

Neo4j/Cypher

MongoDB Atlas

Job description

• Design and develop AI/LLM-powered applications and agentic workflows.
• Build RAG and GraphRAG solutions using knowledge graphs, vector search, and embeddings.
• Develop multi-stage AI agent workflows with reliable state management and traceability.
• Build MCP tool servers and A2A interfaces.
• Implement prompt engineering, structured outputs, and tool/function calling.
• Develop AI evaluation frameworks, guardrails, and anti-hallucination controls.
• Build and maintain CI/CD pipelines and production AI infrastructure.
• Implement monitoring, logging, tracing, and observability.
• Collaborate with engineering and business teams to deliver enterprise AI solutions.

Required Skills

• 6-10 years of software engineering experience with hands-on production AI/LLM experience.
• Experience with GenAI, LLMs, RAG, and Agentic AI.
• Experience with prompt engineering, structured/JSON outputs, and tool/function calling.
• Experience with knowledge graphs, vector search, and embeddings.
• Experience with Neo4j/Cypher and/or MongoDB Atlas.
• Knowledge of MCP, A2A, or AI agent interfaces.
• Experience with cloud infrastructure, CI/CD, monitoring, and observability.
• Strong Git, code review, and automated testing practices.