Architect – Enterprise AI

Stellenbeschreibung:

Define enterprise architecture standards, reference architectures, and implementation patterns for AI, Agentic AI, and AI-enabled solutions
Partner with Enterprise Architecture, Engineering, Data, Security, and business teams to evaluate AI use cases and provide guidance on architectural tradeoffs
Design and maintain reusable architecture patterns for AI gateways, Model Context Protocol (MCP) integrations, agent orchestration, enterprise knowledge access, retrieval architectures, and AI platform services
Establish architectural guidance for AI security, identity management, authorization, governance, compliance, and policy enforcement
Support adoption of AI development lifecycle (AI-DLC) practices through architecture reviews, standards, reference implementations, and implementation guidance
Define architectural approaches for AI evaluation, observability, monitoring, operational readiness, and cost management
Develop reference implementations and proof-of-concept solutions to accelerate delivery and scale AI capabilities into production environments
Ensure AI and technology solutions align with enterprise architecture standards, strategic technology roadmaps, and long-term operational objectives
Collaborate with stakeholders to gather, analyze, communicate, and validate requirements impacting ALSAC's enterprise technology environment

Requirements

Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field
10+ years of experience in enterprise architecture, solution architecture, systems integration, software engineering, or related technology disciplines
Experience designing and implementing AI, Generative AI, machine learning, or intelligent automation solutions
Experience developing architecture standards, reference architectures, and technology governance practices
Strong understanding of cloud platforms, application integration, enterprise security, and modern software architecture patterns
Ability to communicate technical concepts effectively to both technical and non-technical stakeholders
5+ years of leadership, team lead, or architecture influence experience
Preferred: Enterprise AI architecture expertise with Bedrock, MCP, AI Gateways, LangGraph/LangChain, RAG, and agentic AI platforms
Preferred: Strong architecture and implementation experience across OpenShift/Kubernetes and scalable AI infrastructure, including deployment, operations, and lifecycle management of long-running agents
Preferred: Knowledge of large language models (LLMs), retrieval-augmented generation (RAG), agent frameworks, vector databases, and AI observability practices
Preferred: Experience with responsible AI, AI governance, security, and compliance frameworks
Preferred: Experience creating reusable frameworks, accelerators, and architecture guidance for enterprise technology teams

Core Competencies

Demonstrates expertise in defining enterprise architecture standards and implementing AI solutions, with a strong focus on AI security, governance, and compliance. Proven ability to collaborate with cross-functional teams to drive AI adoption and align technology solutions with strategic objectives.