Artificial Intelligence Engineer

Canada
Remote
Posted Nov 4, 2026
1 position

$75–$100 / hour

Opens LinkedIn

Employment type: Contract
Posting language: English
Location requirements: Country, Toronto, Ontario, Canada
Application method: Apply on LinkedIn (LinkedIn sign-in required)

Job summary

Build, host, and improve production LLM agents and retrieval systems for HR and payroll testing, including secure Azure deployment, evaluation, and integrations with Azure DevOps and Microsoft 365. Run automation pipelines on requirements and test workbooks, validate and reconcile outputs for review, and prototype additional AI applications across HR and pay processes.

Job details

Agentic AI Engineer — HR & Pay Automation Introduction Brunel is currently seeking a Agentic AI Engineer to support a government project on a remote (EST hours in Canada) Contract role. Role summary We are building AI-assisted automation for a large HR and payroll programme: agents and pipelines that turn business requirements and test-case workbooks into test cases, validated staging data and reviewer-ready evidence. The core is already working and in use. We need a hands-on AI engineer to build, host and enhance these agents with us, take on delivery work using them, and bring new ideas on what AI can do next for HR and Pay. This is a developer role. The person writes production code, measures what it does, and ships. What you will do Build agents. Design and implement LLM-based agents and tools: tool and function calling, structured outputs, multi-step workflows, human-in-the-loop approval, prompt and context design. Build the tool layer. Extend our MCP (Model Context Protocol) server and APIs that agents call to read requirements, agreements, process maps, reference test cases and product documentation. Host and operate. Take agents from a local, single-user setup to a hosted service: containerized backend, identity and access control, audit logging, secrets management, deployment on Azure. Retrieval and knowledge. Build retrieval over HR and pay documents (collective agreements, process catalogues, test libraries): chunking, embeddings, hybrid search, re-ranking, with measured retrieval quality. Evaluate. Build labelled evaluation sets and regression tests for every AI feature; report accuracy, precision and recall; keep deterministic logic deterministic where a rule beats a prompt. Integrate. Connect outputs to Azure DevOps test management, and build Microsoft 365 agents (Copilot Studio, Agent Builder, Power Automate, Teams, SharePoint) for reviewer feedback and Q&A inside the tenant. Deliver with the tooling. Run the pipelines on new requirement workbooks, resolve what they flag, reconcile counts, and prepare outputs for review. Bring ideas. Propose and prototype new uses of AI across HR and pay testing: coverage analysis, scenario generation, defect triage, process-to-requirement mapping. Must-have skills Python, 5+ years. Production code on a shared codebase: typing, pytest, git branches and pull requests, code review. LLM application engineering, 12+ months shipped. Direct experience with at least one major model API (Anthropic, OpenAI, Azure OpenAI): tool use, structured output, streaming, token and cost management, prompt caching. Agentic systems. Built multi-step agents with tools, memory and approval gates; familiar with MCP and at least one agent framework or SDK. Retrieval (RAG). Embeddings, vector stores, hybrid search, chunking strategy, and how to evaluate retrieval before building on it. Evaluation. Labelled datasets, metrics, regression suites for non-deterministic systems; can explain why a number moved. Backend and hosting. FastAPI or equivalent, Docker, REST, authentication and authorization, logging, deployment to Azure (App Service, Container Apps or AKS), CI/CD. Data handling. Messy multi-sheet Excel and CSV at scale with openpyxl or pandas; reconciliation that adds up; SQL. AI-assisted development. Works fluently with AI coding assistants day to day and reviews their output critically. Communication. Clear written English; documents what a system understood and what it refused; drafts precise questions when something is unclear. Able to work with Government of Canada data: Reliability Status held or obtainable. Nice-to-have skills Microsoft 365 agent stack: Copilot Studio, Agent Builder, Power Automate, Power Platform, Azure AI Foundry, Semantic Kernel or Autogen. Azure DevOps: test plans, suites, work items, REST API. HCM or payroll platforms (Dayforce, Workday, SAP SuccessFactors, PeopleSoft) or public-sector HR and pay, including collective agreements and classification. Test engineering: test design, coverage, traceability, staging data. Document AI: PDF and image extraction, OCR, Visio or diagram parsing. Observability for LLM apps: tracing, evaluation dashboards, cost reporting. Security for AI systems: prompt injection defense, data boundaries, tenant DLP. French. What We Offer Why work with Brunel? We are proud to offer exciting career opportunities from over 100 offices globally in 42 countries. Advancing your career takes time and effort – let us match you to your ideal position. About Us Brunel has a reputation for working with some of the best in the business. That’s what we continually strive for. Brunel provides the global recruitment and workforce services you need to lead your industry. With 50 years of market experience in Renewable Energy, Automotive, Oil & Gas, Life Sciences, Mining and Infrastructure, we help you finish major projects safely, compliantly, on-time, within budget and at the highest quality, so you can keep growing – anywhere in the world.

What you’ll do

Requirements

Requires 5+ years of Python experience and at least 12 months of shipped LLM application engineering, including production coding practices, agentic workflows, model APIs, retrieval, and evaluation. Candidates should also have backend and Azure deployment experience, strong data-handling and SQL skills, clear written English, and the ability to work with Government of Canada data with Reliability Status held or obtainable.