Friends, we are at a once‑in‑a‑generation inflection point. Every organization is talking about AI, but very few are actually making it real. This role sits at the center of that moment:
As an AI & Automation Engineer at Invero, you’ll help organizations move from AI curiosity to real‑world impact. This isn’t a research role or a demo factory – you’ll be embedding AI directly into the workflows people rely on every day, helping businesses adopt, govern, and trust AI responsibly.
We’re hiring an AI & Automation Engineer to own post‑workshop execution and turn prioritized AI opportunities into working solutions inside real client environments. This is a hands‑on builder‑operator role where you’ll take ideas emerging from AI Envisioning Workshops and Copilot training and bring them to life – designing, building, and deploying solutions that actually get used.
(Please note: this role is open to candidates based in Canada with legal authorization to work here.)
Responsibilities
Primary focus:
-
Build and configure AI-enabled solutions that improve real workflows and outcomes. This may include:
-
Microsoft Copilot Studio / Power Platform solutions
- Azure-based AI solutions (e.g., Azure OpenAI / Azure AI Foundry) when use cases require more flexibility and developer control
Secondary focus
-
Identify data opportunities that unlock AI outcomes and help drive pragmatic execution when needed (e.g., data readiness, structure, access, lightweight transformations).
Day to Day
1) Build and configure AI-enabled solutions (Primary)
-
Build, configure, and iterate AI-enabled solutions using the most appropriate approach for the use case:
-
Copilot Studio / Power Platform for fast, governed workflow automation and M365-grounded experiences
- Azure AI (Azure OpenAI / Azure AI Foundry and related services) for deeper integrations, custom orchestration, advanced retrieval (RAG), and scenarios requiring more developer control
- Design practical end-user experiences where AI shows up inside real work (e.g., Teams, SharePoint, web apps, business workflows).
- Ship v1 quickly, then iterate based on user feedback and observed outcomes.
2) Own execution and client momentum (Primary)
-
Lead execution engagements following workshops and/or Copilot training.
- Run working sessions with business + IT stakeholders to clarify scope, define success metrics, and unblock dependencies.
- Operate with disciplined delivery hygiene:
- Maintain a prioritized delivery backlog
- Limit work-in-progress to protect focus and quality
- Define clear milestones and decision gates
- Show visible progress each month (working artifact or a confident “stop / not worth it” decision)
3) Apply “minimum viable guardrails” while moving fast (Primary)
-
Recognize common risk areas and readiness issues (oversharing, unclear data boundaries, unsafe tool usage patterns).
- Embed practical guardrails into delivery without slowing the business down.
- Escalate to senior advisors when complexity, risk, or architecture warrants it.
4) Identify and help execute data opportunities (Secondary)
-
Identify data gaps that block AI outcomes (availability, structure, access, ownership, quality).
- Recommend pragmatic fixes that improve readiness and reliability.
- Where appropriate, help execute lightweight data work such as:
- Organizing and structuring content for retrieval (SharePoint/Teams structure)
- Basic data extraction/feeds (exports, connectors, structured inputs)
- Light transformation/cleanup steps
- Coordinating with client IT/data teams or vendors when deeper work is needed
This is not a pure data engineering role, but you should be comfortable diagnosing data readiness issues and driving practical remediation to enable delivery.
5) Create repeatable delivery patterns and assets (Primary)
-
Capture reusable patterns, templates, and checklists:
- “Ready” criteria
- Test scripts / evaluation sets
- Rollout and adoption playbooks
- Prompt patterns and agent design conventions
- Document learnings and continuously improve how we deliver post‑workshop outcomes.
Qualifications
Proven experience delivering end-to-end client solutions (consulting, implementation, solutions engineering, product delivery, or similar).
-
Hands-on capability in at least two of the following areas:
-
Building AI assistants/agents (Copilot Studio preferred, or similar platforms)
- Power Platform delivery (Power Automate; Power Apps is a plus)
- M365 delivery experience (SharePoint/Teams; permissions and sharing concepts)
- API-based integration experience (basic to intermediate)
- Data estate modernization and enablement
-
Strong execution judgment:
-
Ships v1 quickly, iterates often
- Manages scope and expectations
- Closes loops and shows outcomes
- Strong communication skills with business stakeholders (clear, pragmatic, non-jargony).
NICE-TO-HAVE:
- Familiarity with Azure building blocks (Functions, Logic Apps, storage, identity patterns).
- Familiarity with Azure-based AI patterns and when they’re appropriate (Azure OpenAI / Azure AI Foundry).
- Light analytics/data background (Power BI, data modeling basics, structured vs unstructured considerations).
- Awareness of AI governance concepts (agent sprawl, ownership, lifecycle, safe boundaries).
- Experience in a Microsoft partner / professional services environment.
Working Style & Attributes We Value
-
Bias to action: you make progress without perfect information.
- Builder mindset: you like being in the weeds and making things work. \
- Product instincts: you think in workflows and user outcomes, not just tools.
- Disciplined execution: protect focus, prevent scope creep, ship outcomes.
- Good judgment: know what to do now vs what needs deeper review.
- Client empathy: you can guide clients without overwhelming them.
Please send your resume and cover letter to [email protected].
About Invero
Invero is a boutique Microsoft Solutions Partner and trusted advisor to enterprise IT and business leaders. We act as the enterprise architects of the cloud – helping organizations design, govern, and optimize their Microsoft environments across Modern Work, security and compliance, Azure, data, and AI. Our work spans strategy through execution, with deep expertise in Microsoft licensing and commercial optimization, ensuring clients not only build the right solutions, but license and operate them effectively at scale.
