Agentic AI Specialist
Canada
Fulltime: 40 hrs a week
Experience: 6-9 Years
Education Level: Professional Bachelor
Information Technology
Introduction
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.
What are you going to 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: containerised 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.
* 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: containerised 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.
Essential skills and knowledge
* 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 authorisation, 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.
Nice-to-have skills* Azure DevOps: test plans, suites, work items, REST API.
* HCM or payroll platforms (Dayforce, Workday, SAP SuccessFactors, PeopleSoft) or public-sector HR and pay.
* 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 authorisation, 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.
Nice-to-have skills* Azure DevOps: test plans, suites, work items, REST API.
* HCM or payroll platforms (Dayforce, Workday, SAP SuccessFactors, PeopleSoft) or public-sector HR and pay.
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.
Closing: 05 December 2026
Are you the perfect match for this vacancy? Apply in 5 minutes and let's get in touch!
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Process of your application
Application process & contact
We will now begin examining your application: We will take a close look at your application documents and ask you for additional information if necessary. If your qualifications match our requirements, we will invite you to meet us for the first time.
Project discussion with our customer
If the introductory meeting goes well for you and us, we will arrange a meeting with the customer who has the perfect project for you. This gives you the opportunity to find out more about the customer and the project.
The decision
If you enjoyed the project discussion and the customer is also convinced of your expertise, we will ask you the final and decisive question: Do you want to get started at Brunel?
Introductory conversation with Brunel
In an introductory meeting, we would like to find out more about your interests, ambitions and professional developments. At the same time, we report on working at Brunel and provide information about all career opportunities and prospects.
Welcome to Brunel
Now great times are beginning! With Brunel you have countless opportunities to help shape technological progress. You decide how your career path goes. We support you in every phase of your career. You always have security behind you: Brunel!