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Senior AI Engineer

  • Toronto, ON, Canada

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Original job description

Job Title: Senior AI Engineer

Job Location: Toronto,Ontario-3days per week in office Required-Hybrid

Job Type:Long Term Contract

Mandatory Skills:

  • JVM Engineering (Java/Kotlin)
  • Knowledge Graphs (Neo4j, Cypher, GraphRAG)
  • MCP (Model Context Protocol)
  • Production Platform Engineering (CI/CD, Docker, Kubernetes, Observability)
  • Document Generation & Rendering (Apache POI, PDFBox, pptxgenjs, Office Open XML, Word/PPT/PDF generation, template management).

Required Qualifications

These apply to everyone we will consider.

  • 6-10 years building production software, including recent hands-on delivery of AI or large-language-model systems beyond prototypes.
  • Strong JVM engineering (Java; Kotlin or Scala a plus) with solid practices: Git workflows, code review, automated testing, structured logging, and clean design.
  • Hands-on experience with modern GenAI patterns: prompt engineering, structured or JSON outputs, tool and function calling, retrieval-augmented generation, and agentic workflows.
  • Experience designing and querying a graph or document database (Neo4j and Cypher, or MongoDB Atlas) and using vector search and embeddings for semantic retrieval.
  • A track record of owning your own delivery path: you have taken something you built through a pipeline into production and operated it, rather than handing it over.
  • Practical experience evaluating non-deterministic systems: test design, quality scoring, regression suites, and translating evaluation into business-ready acceptance criteria.
  • Demonstrated ability to design and explain solution architecture (data flow, runtime flow, interfaces, failure modes, and controls) and to explain model behaviour, limitations, and trade-offs in plain language.

And real strength in one of these two adjacent areas

  • Platform and reliability: a major cloud (Azure preferred), containerized deployment with Docker and Kubernetes, CI/CD, observability, and automated quality gates on a service you ran in production.
  • Deliverable generation and rendering: producing Word, PowerPoint, PDF, or Excel output programmatically with libraries such as Apache POI, PDFBox, or pptxgenjs, making that output deterministic and testable, and moving comfortably between a JVM service and a Node.js rendering toolchain.

Preferred Qualifications

  • Experience with the Model Context Protocol (MCP), building tool or resource servers and clients, and with agent-to-agent (A2A) interoperability.
  • Experience integrating with low-code agent platforms such as Microsoft Copilot Studio.
  • Experience with event-sourced or workflow frameworks (for example, the Akka SDK, Temporal, or similar) for long-running, restart-safe processes.
  • Experience with cloud AI services (for example, Azure OpenAI or Azure AI, or equivalent), GraphRAG, and document-intelligence or OCR pipelines.
  • Experience building conformance, golden-output, or contract-test harnesses.
  • Comfort across languages: Python and Bash for tooling, and the ability to read a Node.js codebase as readily as a JVM one.
  • Familiarity with Office Open XML internals, or with rendering diagrams and charts programmatically (SVG, layout engines such as elkjs, or headless rendering).
  • Experience implementing GenAI guardrails and delivering under formal AI or model-risk governance.
More about this job

Responsibilities

Build and operate production AI and large-language-model systems, including graph- and document-based retrieval, agent workflows, and integrations. Design reliable platform or document-generation solutions, and evaluate their quality, failure modes, and controls for production use.

Requirements

Requires 6–10 years of production software experience, strong JVM engineering, hands-on delivery of AI/LLM systems, and experience with databases, embeddings, and retrieval. Candidates must have owned production delivery and be able to evaluate non-deterministic systems and explain solution architecture; strength in platform reliability or programmatic document generation is also required.

Skills

  • Java
  • Kotlin
  • JVM Engineering
  • Knowledge Graphs
  • Neo4j
  • Cypher
  • GraphRAG
  • Model Context Protocol
  • Generative AI
  • Retrieval-Augmented Generation
  • Vector Search
  • Docker
  • Kubernetes
  • CI/CD
  • Observability
  • Document Generation

Visa sponsorship

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Categories

  • Technology
  • Software
  • Engineering
  • Data & Analytics

Keywords

  • Java
  • Kotlin
  • Scala
  • JVM
  • Neo4j
  • Cypher
  • MongoDB Atlas
  • Knowledge Graphs
  • GraphRAG
  • Model Context Protocol
  • Agent-to-Agent Interoperability
  • Generative AI
  • Large Language Models
  • Prompt Engineering
  • Structured Outputs
  • Tool Calling
  • Retrieval-Augmented Generation
  • Vector Search
  • Embeddings
  • Azure
  • Azure OpenAI
  • Docker
  • Kubernetes
  • CI/CD
  • Observability
  • Apache POI
  • PDFBox
  • pptxgenjs
  • Office Open XML
  • Temporal

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