Role: Senior AI Engineer

Location: Toronto, ON (Hybrid-3 days/Week)

Duration: 6-12 Months Contract with possible extension

Summary:

Seeking a Senior AI Engineer with strong experience in Agentic AI, LLMs, RAG, Python, cloud platforms, and enterprise AI solutions. The role focuses on building scalable AI systems, knowledge-driven applications, and production-ready AI platforms.

Key Responsibilities:

Design and Build Agentic AI Workflows-

- Architect and develop long-running, multi-stage AI-driven analytical workflows that can pause, resume, recover, and maintain state throughout execution.
- Orchestrate large language models (LLMs) alongside tools for retrieval, reasoning, calculations, business rules, and structured data extraction.
- Develop robust prompt engineering strategies and structured output frameworks to ensure validated, machine-consumable responses.
- Build solutions on event-driven and event-sourced architectures, ensuring decisions, evidence, workflow states, and results are persisted throughout the process.
- Deliver transparent and traceable AI workflows that provide explainability and auditability.

Build and Operate Enterprise Knowledge Graphs-

- Design, implement, and maintain knowledge graph solutions using technologies such as Neo4j, MongoDB Atlas, or similar platforms.
- Develop ingestion, extraction, and transformation pipelines that convert unstructured documents into validated and searchable knowledge models.
- Ensure all extracted data includes provenance and source attribution.
- Implement GraphRAG, vector search, embeddings, and hybrid retrieval strategies to provide grounded and evidence-based AI responses.
- Optimize graph architecture for performance, scalability,



and business usability.

Develop Open Agent Interfaces and AI Integrations-

- Build Model Context Protocol (MCP) tool servers and Agent-to-Agent (A2A) interfaces that allow AI capabilities to be consumed by external systems and multi-agent ecosystems.
- Integrate AI services with Microsoft Copilot Studio, low-code platforms, and conversational AI solutions.
- Design conversational interfaces that leverage grounded enterprise knowledge while maintaining response accuracy and trustworthiness.
- Enable business users to query enterprise knowledge assets and trigger analytical workflows through natural language interactions.

Establish AI Governance, Evaluation, and Safety Standards-

- Implement comprehensive anti-hallucination controls to ensure all AI-generated outputs are sourced, validated, and explainable.
- Build evaluation frameworks including regression testing, section-level scoring, edge-case validation, and human-review workflows.
- Create measurable acceptance criteria and quality standards for AI solutions.
- Implement guardrails for prompt injection protection, secure data handling, privacy compliance, and safe output generation.
- Partner with governance and risk teams to produce documentation and evidence required for AI model reviews and compliance processes.

Productionize and Manage AI Platforms-





- Own end-to-end deployment processes from development through production.
- Develop and maintain CI/CD pipelines, infrastructure automation, environment configuration, secrets management, and access controls.
- Manage integrations with cloud-based AI services including:
- Foundation and hosted models
- Search and retrieval services
- Document repositories
- OCR and document intelligence platforms
- Vector databases and knowledge graph solutions
- Establish comprehensive observability practices, including logging, monitoring, distributed tracing, alerting, and operational analytics.
- Drive reliability, scalability, and operational excellence across AI platforms and services.
- Establish comprehensive observability practices, including logging, monitoring, distributed tracing, alerting, and operational analytics.
- Drive reliability, scalability, and operational excellence across AI platforms and services.

Required Skills:

- 7+ years of Software Engineering experience.
- 3+ years of Generative AI / AI-ML experience.
- Strong experience with Python.
- Hands-on experience with LLMs, Agentic AI, and Prompt Engineering.
- Experience with LangChain or similar AI frameworks.
- RAG, Embeddings, and Vector Database experience.
- API development and AI integrations.
- Cloud experience (AWS and/or Azure).
- CI/CD and software development best practices.
- Solid communication and stakeholder collaboration skills.

Preferred Skills:

- MCP (Model Context Protocol).
- Multi-Agent Systems.
- Neo4j, GraphRAG, Knowledge Graphs.
- Microsoft Copilot Studio.
- AI Governance and Responsible AI.
- Experience in regulated industries.

📌 Senior AI Engineer (Ontario)
🏢 IMCS Group
📍 Ontario