Microsoft AI & Automation Architect

• Ready to own the architecture and governance of an enterprise agent practice, from the first qualification decision through to production operations?
• Do you want to shape enterprise AI strategy by selecting and designing the right solutions for complex business challenges?
• Is your next step a customer-facing architecture role where you design secure, responsible, and scalable AI solutions at a global leader in software and cloud solutions?

Location: Sofia, Bulgaria | Reports to: Service Delivery Lead - Azure & DWP| Work Arrangement: Hybrid | Language Requirements: Fluent / professional English, written and verbal | Learn more:

As our new Microsoft AI & Automation Architect, you will lead the technical and governance design of our agent delivery practice. You own the classification and sizing model that turns customer demand into scoped, deliverable work; you design the identity, data-protection and evaluation posture that every agent ships with; and you architect the complex builds yourself on Microsoft Copilot Studio and Microsoft Foundry.

This is a customer-facing architecture role on large enterprise AI enablement engagements, working alongside strategy, security and adoption workstreams. Alongside pre-sales and hands-on delivery, you will help ensure that Responsible AI and governance principles are designed into solutions from the beginning rather than added at the end.

We care more about solving the problem than using the most powerful technology.

Key Responsibilities

• Own the platform decision for each enterprise AI use case — Copilot Studio, Microsoft Foundry or the Power Platform — working from the business outcome rather than the product, choosing the least powerful option that meets the requirement, and defending that trade-off in design review
• Say so when the answer is not an agent at all: structured, predictable work belongs in deterministic automation, and static retrieval in classic search. Recommending that is part of the job
• Use agile and design-thinking methods to uncover, challenge and prioritise valuable AI and automation use cases
• Size and scope agent use cases against a published classification framework; own the estimate and sign off the scope
• Design the per-agent security model: agent identity in Microsoft Entra, least-privilege permission scopes, Conditional Access treatment, and placement of human approval gates on write-actions
• Define the data-protection checklist for each agent — sensitivity labels and DLP behaviour across grounding sources and action paths — and route findings into the appropriate remediation track
• Architect complex and autonomous builds end to end: solution design on Copilot Studio, Microsoft Foundry, custom connectors and API integration, entitlement design, environment and subscription structure, and cost model
• Run AI-specific threat modelling for high-autonomy agents, validating the existing threat framework against MITRE ATLAS and the OWASP generative-AI risk lists, and plan adversarial testing
• Define the evaluation method for every agent — grounding-quality question sets, functional test cases, acceptance thresholds — and approve results before go-live
• Design and advise governance guardrails within the customer's Power Platform — managed environments, DLP connector policies, the custom connector approval route, capacity and license consumption, and the Center of Excellence tooling that keeps the estate visible
• Own the environment strategy and the deployment process across development, test and production
• Lead effort calibration and change-control conversations with customers as delivery data accumulates
• Mentor agent engineers, own their skilling plan, and contribute reference architectures, patterns and playbooks and other reusable assets