Senior AI Architect - Microsoft Technologies

EPAM Systems; Indiana (PA); Hybrid; USD 120,000 - 160,000; Full time

Job summary

EPAM Systems is seeking a Senior AI Architect for a hybrid role based in Pennsylvania, Indiana. You will drive enterprise-scale AI transformations, designing and implementing AI platforms primarily on Microsoft Azure.

The ideal candidate will have over 10 years of experience in solution architecture and AI-native engineering. Key responsibilities include defining target-state architectures, leading technical roadmaps, and collaborating with cross-functional teams to deliver AI systems integrated into workflows.

Qualifications

• 10+ years in solution architecture, cloud platforms or platform engineering.
• Strong experience with enterprise AI, GenAI, and AI-native engineering.
• Proficiency with Microsoft Azure and modern cloud-native architecture.

Responsibilities

• Define target‑state architectures for AI platforms and workflows.
• Lead architecture discovery and technical roadmaps.
• Design Azure-first architectures using Azure OpenAI and other services.

Skills

Solution architecture

Enterprise AI

Microsoft Azure

GitHub workflows

AI-native engineering

Tools

Azure Functions

PostgreSQL

Terraform

Job description

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
• Nice to have: Familiarity with agent frameworks such as Semantic Kernel, LangChain, LangGraph, AutoGen, LlamaIndex, CrewAI or similar
• Nice to have: Knowledge of Microsoft 365 Copilot, Copilot Studio, Microsoft Graph, Teams, SharePoint or Power Platform integration
• Nice to have: Understanding of AI gateways, model routing, semantic caching, model abstractions, usage telemetry and AI FinOps
• Nice to have: Background in enterprise infrastructure with Terraform/IaC, Kubernetes/AKS, CI/CD and secure API gateway practices
• Nice to have: 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
• Nice to have: Familiarity with compliance and governance standards such as GDPR, EU AI Act readiness or ISO/IEC 42001
• Nice to have: Experience in regulated industries such as finance, healthcare, energy, retail, manufacturing or public sector
• Nice to have: Knowledge of other AI ecosystems, including AWS Bedrock, Google Vertex AI, Databricks, Snowflake, Anthropic, OpenAI API or Hugging Face