Solution Architect - LangGraph & Agentic AI

We are looking for an experienced Solution Architect with hands-on experience designing and deploying LangGraph-based AI solutions to lead the architecture of enterprise agentic AI platforms and applications. You will work with business and technology stakeholders to identify high-value AI opportunities and translate them into secure, scalable, and production-ready architectures. The role combines AI architecture, enterprise integration, cloud engineering, agentic AI, security, governance, and stakeholder leadership. You will be expected to understand LangGraph at a practical level and be able to challenge architectural decisions, guide engineering teams, and ensure that AI solutions can operate reliably at enterprise scale. Requirements AI Solution Architecture " Lead the architecture and design of enterprise AI agent and agentic workflow solutions. " Design LangGraph-based architectures for single-agent and multi-agent applications. " Translate business requirements, processes, SLAs, security requirements, and technical constraints into solution architectures. " Evaluate architectural alternatives and document key technical decisions and trade-offs. " Define reusable architecture patterns for agentic AI solutions. Enterprise Agent Architecture " Design architectures incorporating: " LLMs " LangGraph " RAG " Enterprise data " APIs and business systems " Workflow engines " Human approval processes " Observability " Security and governance " Define appropriate boundaries between AI reasoning and deterministic business logic. " Design state management, persistence, recovery, and long-running agent workflows. " Determine when to use single-agent, multi-agent, or conventional application architectures. Cloud and Platform Architecture " Design scalable AI application architectures on AWS, Azure, or GCP. " Define compute, networking, storage, API, security, and platform requirements. " Design architectures suitable for enterprise-scale production workloads. " Evaluate cloud services and AI platform capabilities based on performance, security, scalability, and cost. " Work with platform engineering and DevOps teams to establish deployment standards. Integration Architecture " Design integration between AI agents and enterprise applications, APIs, databases, and SaaS platforms. " Define secure mechanisms for agent tool access and business-system interactions. " Design authentication, authorisation, secrets management, and access-control approaches. " Ensure AI-driven actions are traceable, auditable, and appropriately governed. AI Security and Governance " Establish security and governance principles for enterprise AI agents. " Address risks including: " Prompt injection " Data leakage " Unauthorised tool usage " Excessive agent permissions " Inaccurate or unsafe actions " Sensitive-data exposure " Define appropriate human-in-the-loop controls. " Ensure solutions comply with organisational security, privacy, regulatory, and responsible-AI requirements. AI Evaluation and Observability " Define architecture for AI application monitoring and observability. " Establish approaches for evaluating agent accuracy, reliability, latency, cost, and task completion. " Define appropriate logging, tracing, metrics, and alerting. " Establish operational processes for monitoring and continuously improving production agents. Stakeholder and Technical Leadership " Work directly with senior business and technology stakeholders to define AI strategies and roadmaps. " Lead architecture workshops and technical design sessions. " Communicate complex AI concepts and architectural trade-offs to technical and non-technical audiences. " Provide technical direction to AI engineers, developers, data teams, and platform engineers. " Review solution designs and ensure alignment with enterprise architecture standards. " Mentor engineering teams and promote reusable AI architecture patterns. Required Experience " Significant experience in solution architecture, software architecture, AI architecture, or a related role. " Hands-on experience designing and deploying LangGraph-based AI applications or agentic workflows. " Strong understanding of LLM application architectures. " Experience with enterprise AI/ML solutions in production. " Strong understanding of RAG, tool calling, agent orchestration, and human-in-the-loop patterns. " Strong experience with at least one major cloud platform: AWS, Azure, or GCP. " Strong understanding of enterprise integration patterns and APIs. " Experience with security, governance, observability, and operational requirements for production systems. " Strong technical understanding of Python and modern software engineering practices. Desirable Experience " LangChain / LangSmith " Multi-agent architectures " Enterprise RAG platforms " Vector databases " Kubernetes " Event-driven architectures " Microservices " Infrastructure as Code " CI/CD " MLOps / LLMOps " AI security " Responsible AI " Large-scale enterprise transformation " Experience working directly with senior client stakeholders Find Jobs in France on Arbeitnow