Senior AI Architect - Microsoft Technologies

Location: Zürich

We're looking for a Senior AI Architect to join our team in Switzerland in a hybrid working mode. In this role, you will help clients design and scale production-grade AI platforms and solutions on Microsoft Azure. You will work at the intersection of enterprise architecture, cloud-native engineering, Git Hub-enabled software delivery and responsible AI adoption.

This position focuses on shaping large-scale AI transformation programs that connect business outcomes with practical architecture design. You will engage in areas such as Azure AI platforms, copilots, RAG, agentic systems, governance, observability, evaluation, security and Responsible AI practices.

Unlike roles centered on proofs of concept, this opportunity involves delivering enterprise-grade AI systems embedded into real workflows, including engineering productivity, knowledge retrieval, automation and AI-enabled delivery. The challenges go beyond basic API calls and span AI-native software engineering, Git Hub Copilot integration, secure architectures, Fin Ops and governance  will collaborate with architects, engineers, Microsoft/Git Hub specialists and client leadership teams to drive secure and governed AI adoption.

Responsibilities Define target-state architectures for AI platforms, assistants, RAG systems, agents, AI gateways and AI-native engineering workflows

Lead architecture discovery, maturity assessments, technical roadmaps, platform decisions and delivery governance

Design Azure-first architectures using Microsoft Foundry, Azure OpenAI, Azure AI Search, Azure API Management, AKS, Azure Functions, Application Insights, Azure Monitor, Key Vault, Microsoft Entra , Cosmos DB, PostgreSQL and Microsoft Fabric where applicable

Design AI-native engineering systems using Git Hub Copilot, Git Hub Enterprise, Git Hub Advanced Security, agent-ready repositories, secure pull-request practices and AI-assisted delivery patterns

Design harnesses around AI systems, including agent instructions, tool contracts, MCP integrations, retrieval grounding, evaluation suites, telemetry, cost controls, policy controls and human approval gates

Define governance and operational frameworks for Responsible AI, security, identity, Fin Ops and observability

Translate business outcomes into target architecture, executive narratives, platform decisions and delivery governance across client leadership, architecture, engineering and security teams

Facilitate workshops, hackathons and enablement sessions focused on AI adoption, Copilot integration and engineering excellence

Convert practical experience into reusable patterns, accelerators and architectural blueprints

Mentor architects and engineers and contribute to presales and solution design initiatives Requirements
10+ years in solution architecture, cloud platforms or platform engineering

Strong experience with enterprise AI, GenAI, agentic systems, RAG and AI-native engineering

Proficiency with Microsoft Azure and modern cloud-native architecture

Knowledge of Git Hub workflows (CI/CD, Dev Ops, IaC) and secure engineering practices

Track record of moving AI initiatives beyond PoC to enterprise-grade production environments

Hands-on capability to validate prototypes, review code and guide engineering decisions

Ability to explain how to make AI useful in production, not just impressive in a demo Capability to design platform architecture, governance models, adoption plans and AI delivery workflows

Confidence working across enterprise realities, leveraging Azure and Git Hub pragmatically

Strong communication skills with both executives and technical stakeholders

Nice to have

Experience with Git Hub Copilot Enterprise adoption, AI-native SDLC transformation, Git Hub Actions and Git Hub Advanced Security Familiarity with agent frameworks such as Semantic Kernel, Lang Chain, Lang Graph, Auto Gen, Llama Index, CrewAI or similar

Knowledge of Microsoft 365 Copilot, Copilot Studio, Microsoft Graph, Teams, SharePoint or Power Platform integration

Understanding of AI gateways, model routing, semantic caching, model abstractions, usage telemetry and AI Fin Ops Background  in enterprise infrastructure with Terraform/IaC,…