{"id":2574089,"url":"https://alion.io/job/cognizant-microsoft-azure-agentic-ai-solution-architect","title":"Microsoft Azure Agentic AI Solution Architect","company":{"id":85,"name":"Cognizant","domain":"cognizant.com","url":"https://alion.io/company/cognizant","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Cognizant Careers","truth_index":{"grade":"A","score":87,"open_postings":124,"ghost_share":0,"stale_share":0.694,"repost_share":0.016,"time_to_fill_p50_days":20,"computed_at":"2026-10-22T06:10:10Z"}},"role":"Solutions","role_family":"Solutions","seniority":"staff","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Atlanta, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":85000,"max_usd":165000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":766},"experience_years_min":12,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":".NET","optional":false},{"name":"A2A","optional":false},{"name":"AgentOps","optional":false},{"name":"AI Agents","optional":false},{"name":"Azure","optional":false},{"name":"Azure AKS","optional":false},{"name":"Azure Cosmos DB","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Copilot","optional":false},{"name":"Copilot Studio","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"GitHub","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Java","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"Least Privilege","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"LLMOps","optional":false},{"name":"Microsoft Entra ID","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"OpenAI","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"Rest API","optional":false},{"name":"Semantic Kernel","optional":false},{"name":"ServiceNow","optional":false},{"name":"SQL","optional":false},{"name":"C#","optional":true},{"name":"FinOps","optional":true},{"name":"Red Teaming","optional":true}],"status":"live","first_seen_at":"2026-10-14T15:30:13Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-22T08:42:40Z","board_verified":true,"closed_at":null,"days_open":7,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":7},"description":"Job Description - Microsoft Azure Agentic AI Solution Architect\nPosition Summary\nWe are seeking an experienced Microsoft Azure Agentic AI Solution Architect to lead the architecture, design, and delivery of enterprise-grade Agentic AI and Generative AI solutions on Microsoft Azure. The architect will translate business requirements into secure, scalable, governed, and production-ready AI architectures, taking solutions from discovery and proof-of-concept through industrialized deployment and operations.\nThe role requires strong hands-on architecture expertise across Microsoft Foundry/Azure AI Foundry, Azure OpenAI, multi-agent orchestration, Retrieval-Augmented Generation (RAG), enterprise integrations, cloud-native Azure services, security, Responsible AI, and LLMOps/AgentOps.\nKey Responsibilities\nAgentic AI & GenAI Architecture\nDesign end-to-end Agentic AI architectures using Microsoft Foundry/Azure AI Foundry and Azure OpenAI.\nDefine single-agent and multi-agent patterns including orchestration, planner/executor flows, memory, tool use, reflection, human-in-the-loop approvals, and agent handoffs.\nDesign interoperable agent solutions using patterns and protocols such as MCP and A2A, where appropriate.\nEstablish reusable architecture patterns for agents, prompts, tools, grounding, workflows, and enterprise integrations.\nEvaluate foundation models and orchestration approaches based on accuracy, latency, security, scalability, and cost.\nRAG, Knowledge & Data Architecture\nArchitect enterprise RAG solutions using Azure AI Search and governed enterprise data sources.\nDefine document ingestion, chunking, embeddings, hybrid/vector search, reranking, metadata filtering, and citation/source-traceability patterns.\nDesign permission-aware retrieval and secure grounding across enterprise repositories and APIs.\nApply semantic models, knowledge graphs, ontologies, and Microsoft Fabric capabilities where they add business value.\nAzure Cloud & Integration Architecture\nDesign secure cloud-native solutions using Azure Functions, Durable Functions, Container Apps/AKS, App Service, API Management, Service Bus, Event Hubs, Logic Apps, Storage, Cosmos DB/SQL, and related Azure services.\nIntegrate agents with Microsoft 365, Copilot Studio, Microsoft Graph, Power Platform, ServiceNow, enterprise APIs, SaaS platforms, and data services.\nDefine event-driven and API-led integration patterns for long-running and asynchronous agent workflows.\nSecurity, Governance & Responsible AI\nDefine identity and access architecture using Microsoft Entra ID, Managed Identity, RBAC/PIM, Key Vault, private endpoints, and least-privilege principles.\nEstablish guardrails for prompt injection, data leakage, unsafe tool execution, hallucinations, sensitive information, and high-risk actions.\nImplement human approval and auditable execution for state-changing or sensitive agent actions.\nEnsure alignment with enterprise security, privacy, compliance, Responsible AI, and architecture governance standards.\nAgentOps, LLMOps & Production Readiness\nDefine CI/CD and lifecycle management for prompts, models, agents, tools, knowledge assets, and configurations.\nEstablish evaluation frameworks covering groundedness, relevance, task success, safety, latency, reliability, and cost.\nDesign production observability using Azure Monitor, Application Insights, Log Analytics, tracing, metrics, and audit logs.\nDefine operational patterns for retries, idempotency, failure handling, circuit breakers, model routing, token optimization, drift detection, and cost governance.\nArchitecture Leadership & Delivery\nLead discovery workshops, architecture assessments, solution design, PoCs, and production implementation roadmaps.\nProduce architecture artifacts including HLD/LLD, integration designs, security models, deployment views, and architecture decision records.\nDrive architecture reviews and collaborate with business stakeholders, engineering, data, security, infrastructure, DevOps, and operations teams.\nMentor engineering teams and establish reusable standards and engineering best practices for enterprise Agentic AI delivery.\nProvide technical leadership from ideation through deployment and production support.\nRequired Skills & Experience\n12+ years of overall technology experience with significant solution/enterprise architecture responsibility.\n5+ years designing solutions on Microsoft Azure, including cloud-native, integration, security, and data architectures.\nStrong hands-on experience with Agentic AI, Generative AI, LLMs, RAG, and multi-agent architectures.\nExperience with Microsoft Foundry/Azure AI Foundry, Azure OpenAI, Azure AI Search, and the Azure AI ecosystem.\nExperience with agent frameworks or SDKs such as Semantic Kernel, LangGraph/LangChain, Microsoft agent technologies, or equivalent frameworks.\nStrong understanding of MCP, A2A, tool/function calling, agent orchestration, memory, and human-in-the-loop patterns.\nStrong Azure architecture experience across APIs, messaging, serverless/container platforms, identity, networking, storage, databases, and observability.\nKnowledge of vector databases, embeddings, hybrid retrieval, reranking, knowledge graphs, and enterprise data governance.\nExperience with Python and/or .NET/Java and REST/API-based integration.\nExperience with Docker/Kubernetes, infrastructure automation, Azure DevOps/GitHub, and CI/CD.\nDemonstrated ability to architect secure, resilient, scalable, observable, and cost-efficient production AI solutions.\nStrong communication skills with the ability to engage both senior business stakeholders and engineering teams.\nPreferred Qualifications\nExperience with Microsoft 365 Copilot, Copilot Studio, Microsoft Graph, Fabric IQ/Data Agents, or related Microsoft AI capabilities.\nExperience with regulated or security-sensitive enterprise environments.\nFamiliarity with AI evaluation, red teaming, Responsible AI, LLMOps, AgentOps, and FinOps practices.\nExperience modernizing enterprise applications and integrating AI agents with existing business processes and systems.\nMicrosoft certifications relevant to Azure and Agentic AI, such as AI-103, AB-100, or equivalent architecture credentials, are desirable.\nKey Success Measures\nDelivery of secure, scalable, production-ready Agentic AI solutions aligned to measurable business outcomes.\nReduction in time from AI experimentation to enterprise production deployment.\nHigh levels of agent quality, groundedness, reliability, traceability, and operational observability.\nEffective governance of autonomous actions, enterprise data access, security, and AI risk.\nCreation and adoption of reusable Agentic AI architecture patterns and accelerators across delivery teams.\nSalary and Other Compensation:\nThe annual salary for this position is between $150-160Kdepending on experience and other qualifications of the successful candidate.\nThis position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.\nBenefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:\n· Medical/Dental/Vision/Life Insurance\n· Paid holidays plus Paid Time Off\n· 401(k) plan and contributions\n· Long-term/Short-term Disability\n· Paid Parental Leave\n· Employee Stock Purchase Plan\nDisclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. 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