Key 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.

Required Skills
6–10 years of software engineering experience with hands-on production AI/LLM experience.
Robust Java/JVM engineering 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.
Robust Git, code review, and automated testing practices.

Preferred Skills
Kotlin or Scala
GraphRAG
Microsoft Copilot Studio
Akka SDK
AI evaluation frameworks
AI safety and guardrails
OCR/document intelligence

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📌 Senior Ai Engineer Burnaby
🏢 Pacer Staffing
📍 Burnaby