Senior AI Architect - Microsoft Technologies Job Basel area,Kanton Basel-Landschaft Switzerland,Software Development

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.

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, Kubernetes/AKS, CI/CD and secure API gateway practices
Awareness of agent reliability and security techniques, including workflow state, recovery, tool-permission boundaries, evaluation gates, prompt-injection defense, audit trails, rollback mechanisms and human approval workflows
Familiarity with compliance and governance standards such as GDPR, EU AI Act readiness or ISO/IEC 42001
Experience in regulated industries such as finance,…