Generative AI Systems Architect

EPAM Systems is a global leader in AI transformation engineering and integrated consulting, serving Forbes Global 2000 companies and startups. The company has over thirty years of expertise in custom software, product, and platform engineering, empowering clients to become AI-Native enterprises.

• Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent experience
• 1+ years in architecture roles involving cloud, data, or production Generative AI/LLM systems
• Knowledge of cloud platforms (Azure, AWS, GCP) and Infrastructure as Code tools (Terraform, Bicep, CDK, CloudFormation)
• Competency in containerization and orchestration technologies (Docker, Kubernetes), and API gateways/service meshes
• Proficiency in CI/CD and release management for ML/LLM workloads (Jenkins, GitHub Actions, GitLab CI, Azure DevOps)
• Understanding of Large Language Model platforms like Azure AI Foundry, Azure OpenAI, AWS Bedrock, or Google Vertex AI
• Familiarity with security-by-design principles and compliance frameworks tailored to Generative AI systems
• Advanced proficiency in English (B2+/C1)

• Design enterprise generative AI reference architectures, blueprints, and reusable patterns
• Define multi-cloud platform foundations addressing networking, identity, and secrets management
• Lead efforts in LLMOps/ModelOps, focusing on model evaluation, safety, observability, and rollout strategies
• Create frameworks and governance for agentic systems, including tool governance and the Model Context Protocol (MCP)
• Ensure systems comply with security, risk, and compliance standards, applying Responsible AI principles and PII controls
• Establish strategies for cost efficiency, reliability, and performance using capacity planning and FinOps techniques
• Improve developer experience through CI/CD pipelines, golden paths, templates, and Infrastructure as Code (IaC) techniques
• Collaborate with cross-functional teams to align system requirements with strategic objectives

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