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, GitHub-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, GitHub Copilot integration, secure architectures, FinOps and governance at scale.
You will collaborate with architects, engineers, Microsoft/GitHub 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 ID, Cosmos DB, PostgreSQL and Microsoft Fabric where applicable
- Design AI-native engineering systems using GitHub Copilot, GitHub Enterprise, GitHub 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, FinOps 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 GitHub workflows (CI/CD, DevOps, 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 GitHub pragmatically
- Strong communication skills with both executives and technical stakeholders
Nice to have
- Experience with GitHub Copilot Enterprise adoption, AI-native SDLC transformation, GitHub Actions and GitHub Advanced Security
- Familiarity with agent frameworks such as Semantic Kernel, LangChain, LangGraph, AutoGen, LlamaIndex, 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 FinOps
- 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, healthcare, energy, retail, manufacturing or public sector
- Knowledge of other AI ecosystems, including AWS Bedrock, Google Vertex AI, Databricks, Snowflake, Anthropic, OpenAI API or Hugging Face
Benefits
- 5 weeks of vacation
- EPAM Employee Stock Purchase Plan (ESPP)
- Enhanced parental leave
- Extended pension plan
- Daily sickness allowance insurance
- Employee assistance program
- Global business travel medical and accident insurance
- Learning and development opportunities including in-house training and coaching, professional certifications, and courses
*All benefits and perks are subject to certain eligibility requirements