Solution Architect - LangGraph & Agentic AI

Requirements

• 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 ArchitectureLead the architecture and design of enterprise AI agent and agentic workflow solutionsDesign LangGraph-based architectures for single-agent and multi-agent applicationsTranslate business requirements, processes, SLAs, security requirements, and technical constraints into solution architecturesEvaluate architectural alternatives and document key technical decisions and trade-offsDefine reusable architecture patterns for agentic AI solutionsEnterprise Agent ArchitectureDesign architectures incorporating:LLMsLangGraphRAGEnterprise dataAPIs and business systemsWorkflow enginesHuman approval processesObservabilitySecurity and governanceDefine appropriate boundaries between AI reasoning and deterministic business logicDesign state management, persistence, recovery, and long-running agent workflowsDetermine when to use single-agent, multi-agent, or conventional
  application architecturesCloud and Platform ArchitectureDesign scalable AI application architectures on AWS, Azure, or GCPDefine compute, networking, storage, API, security, and platform requirementsDesign architectures suitable for enterprise-scale production workloadsEvaluate cloud services and AI platform capabilities based on performance, security, scalability, and costWork with platform engineering and DevOps teams to establish deployment standardsIntegration ArchitectureDesign integration between AI agents and enterprise applications, APIs, databases, and SaaS platformsDefine secure mechanisms for agent tool access and business-system interactionsDesign authentication, authorisation, secrets management, and access-control approachesEnsure AI-driven actions are traceable, auditable, and appropriately governedAI Security and GovernanceEstablish security and governance principles for
  enterprise AI agentsAddress risks including:Prompt injectionData leakageUnauthorised tool usageExcessive agent permissionsInaccurate or unsafe actionsSensitive-data exposureDefine appropriate human-in-the-loop controlsEnsure solutions comply with organisational security, privacy, regulatory, and responsible-AI requirementsAI Evaluation and ObservabilityDefine architecture for AI application monitoring and observabilityEstablish approaches for evaluating agent accuracy, reliability, latency, cost, and task completionDefine appropriate logging, tracing, metrics, and alertingEstablish operational processes for monitoring and continuously improving production agentsStakeholder and Technical LeadershipWork directly with senior business and technology stakeholders to define AI strategies and roadmapsLead architecture workshops and technical design sessionsCommunicate complex AI concepts and
  architectural trade-offs to technical and non-technical audiencesProvide technical direction to AI engineers, developers, data teams, and platform engineersReview solution designs and ensure alignment with enterprise architecture standardsMentor engineering teams and promote reusable AI architecture patternsRequired ExperienceSignificant experience in solution architecture, software architecture, AI architecture, or a related roleHands-on experience designing and deploying LangGraph-based AI applications or agentic workflowsStrong understanding of LLM application architecturesExperience with enterprise AI/ML solutions in productionStrong understanding of RAG, tool calling, agent orchestration, and human-in-the-loop patternsStrong experience with at least one major cloud platform: AWS, Azure, or GCPStrong understanding of enterprise integration patterns and APIsExperience with security,
  governance, observability, and operational requirements for production systemsStrong technical understanding of Python and modern software engineering practicesDesirable ExperienceLangChain / LangSmithMulti-agent architecturesEnterprise RAG platformsVector databasesKubernetesEvent-driven architecturesMicroservicesInfrastructure as CodeCI/CDMLOps / LLMOpsAI securityResponsible AILarge-scale enterprise transformationExperience working directly with senior client stakeholders