AI & Agent Engineer: Build Smarter LLM Pipelines

Socket.dev; Toronto; On-site; CAD 120,000 - 180,000; Full time

Job summary

Appnovation Technologies in Canada is seeking an experienced AI / Agent Engineer to join our engineering team. You will build MCP servers and graph-RAG pipelines, enable multi-LLM integrations (Claude, Gemini), and collaborate with product, data, and QA in an agile setting.

The role emphasizes scalable, production-grade code, documentation, and staying current with fast-moving AI tooling; prior consulting and Life Sciences connections are a plus.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or equivalent.
• 5+ years in software engineering, with 2+ years in AI/ML or LLM apps.
• Strong Python, LLM development, and agentic patterns.
• Experience building MCP servers and tools.
• Familiar with RAG systems, vector databases, and embeddings.
• Experience with graph stores like Neo4j or Postgres-based graphs.
• Comfort with multiple LLM providers and CI/CD basics.

Responsibilities

• Build and evolve MCP servers, tools, and skills for multiple LLMs.
• Design graph-RAG pipelines transforming documents into agent-friendly facts.
• Implement retrieval across document, vector-RAG, and graph layers.
• Collaborate with QA to improve answer quality and grounding.
• Write clean production-grade code and participate in reviews.
• Work with product, data, and QA in an agile/sprint model.
• Document designs, prompts, and interfaces for maintainability.
• Monitor deployed agents/models and iterate on performance.
• Stay current with fast-moving LLM tooling.

Skills

Python

LLM dev

MCP servers

Graph-RAG

Vector DB

CI/CD

Git

Education

Bachelor's Degree in CS/Engineering

Tools

Neo4j

Postgres

Docker

Kubernetes

Job description

Appnovation Technologies in Canada is seeking an experienced AI / Agent Engineer to join our engineering team. You will build MCP servers and graph-RAG pipelines, enable multi-LLM integrations (Claude, Gemini), and collaborate with product, data, and QA in an agile setting.

The role emphasizes scalable, production-grade code, documentation, and staying current with fast-moving AI tooling; prior consulting and Life Sciences connections are a plus.