Agentic Platform Architect

Itransition is hiring an experienced Agentic Platform Architect to lead the architecture and evolution of an enterprise-grade Agentic AI platform. The role involves defining the platform vision, establishing architecture standards, and driving the development of scalable, secure, and governed AI capabilities across the organization.

• 12+ years of experience in software engineering, platform engineering, or enterprise technology
• Proven experience in platform architecture and designing enterprise-scale cloud-native platforms
• Strong knowledge of microservices architecture, API-led integration, and distributed systems
• Hands-on experience with public cloud platforms (AWS, Azure, or Google Cloud)
• Solid understanding of security architecture, identity and access management, and enterprise security best practices
• Experience with DevSecOps, CI/CD pipelines, and infrastructure automation
• Experience designing AI/ML or Generative AI platforms in enterprise environments
• Strong understanding of Large Language Models (LLMs), AI agents, orchestration frameworks, and Retrieval-Augmented Generation (RAG)
• Experience establishing architecture standards, governance models, and reusable platform capabilities
• Excellent stakeholder management, communication, and technical leadership skills
• Professional English, both written and spoken

Nice to have:

• Cloud architecture certifications (AWS, Azure, or Google Cloud)
• Experience working in large-scale distributed engineering organizations

• Define and govern the end-to-end architecture of the enterprise Agentic AI platform
• Design the AI Gateway and model access architecture
• Define identity, authentication, authorization, and token management patterns for AI agents
• Establish platform governance, security guardrails, and responsible AI controls
• Define the Agentic SDK, orchestration framework, and reusable engineering standards
• Design knowledge management, memory, and Retrieval-Augmented Generation (RAG) architecture
• Define observability, evaluation, monitoring, and quality assurance frameworks for AI agents
• Design agent deployment, release, and lifecycle management processes
• Drive platform adoption by establishing architecture standards, best practices, and governance
• Provide technical leadership and collaborate with engineering teams to ensure consistent implementation of architectural decisions