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 deliver production AI and large-language-model systems, including graph- or document-based retrieval, agent workflows, and programmatic generation of Word, PowerPoint, PDF, or Excel documents. Own the delivery path through deployment and operation, while designing system architecture, evaluating output quality, and supporting reliability and observability.
Requirements
Requires 6–10 years of production software experience, strong JVM engineering, hands-on delivery of AI systems, and experience with retrieval, databases, and evaluation of non-deterministic systems. Candidates should also have strength in platform reliability or deterministic document generation, and be able to explain architecture, model limitations, and trade-offs clearly.
Skills
- Java
- Kotlin
- Neo4j
- Cypher
- GraphRAG
- Model Context Protocol
- Generative AI
- Retrieval-Augmented Generation
- Vector Search
- Prompt Engineering
- Docker
- Kubernetes
- CI/CD
- Azure
- Document Generation
- Apache POI
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Engineering
- Data & Analytics
Keywords
- Java
- Kotlin
- Scala
- Neo4j
- Cypher
- MongoDB Atlas
- 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
- Docker
- Kubernetes
- CI/CD
- Azure
- Observability
- Apache POI
- PDFBox
- pptxgenjs
- Office Open XML
- Microsoft Copilot Studio
- Temporal
- Document Intelligence
- OCR