Enterprise Application Architect

Job Description

Job Summary:

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Seeking a Senior Enterprise Application Architect with extensive experience in Agentic AI, enterprise integration architecture, cloud-native application design, and enterprise

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architecture governance.

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This is a senior-level, hands-on architecture position responsible for designing AI-enabled enterprise applications, establishing reusable integration

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patterns, developing architecture standards, and supporting the creation and operation of an Architecture Center of Excellence (COE).

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The selected candidate will design solutions involving large language models (LLMs), multi-agent orchestration, Retrieval-Augmented Generation (RAG),

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enterprise APIs, event-driven architectures, and cloud-native technologies across Microsoft Azure, AWS, and hybrid environments.

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The ideal candidate combines deep technical architecture expertise with the ability to establish enterprise standards, lead architecture reviews, influence

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technical direction, and communicate effectively with senior business and technology stakeholders.

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Responsibilities

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Agentic AI & Enterprise AI Architecture

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• Design and establish enterprise reference architectures for Agentic AI, AI enabled applications, and LLM-based solutions.
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• Architect multi-agent systems involving agent orchestration, tool calling, task delegation, and coordinated workflows.
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• Design and implement Retrieval-Augmented Generation (RAG) patterns to integrate enterprise knowledge and data with AI applications.
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• Establish secure integration patterns between AI agents, enterprise applications, APIs, and external services.
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• Define architectural approaches for Model Context Protocol (MCP), eventdriven triggers, and agent-to-system communication.
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• Incorporate human-in-the-loop controls, approval workflows, and appropriate oversight into agentic AI solutions.
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• Establish AI architecture guardrails covering identity, access management, security, auditability, observability, evaluation, and cost optimization.
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• Evaluate architectural alternatives and recommend scalable, secure, maintainable AI solutions for enterprise use cases.
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Enterprise Integration & API Architecture

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• Design and govern enterprise integration architectures involving REST APIs, API-led connectivity, messaging systems, and event-driven integration patterns.
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• Define reusable integration standards supporting legacy applications, SaaS platforms, cloud-native applications, and enterprise systems.
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• Establish API lifecycle management practices, including API design, governance, versioning, security, and gateway strategies.
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• Design secure and scalable integration patterns connecting applications across Azure, AWS, and hybrid environments.
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• Evaluate integration technologies and architectural approaches based on performance, reliability, scalability, security, and maintainability.
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• Guide engineering teams in implementing enterprise integration standards and reusable architecture patterns.
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Architecture Center of Excellence (COE) & Governance

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• Help establish, develop, and operate an enterprise Architecture Center of Excellence (COE).
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• Define and maintain enterprise application architecture standards, integration standards, API guidelines, and AI reference architectures.
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• Develop architecture governance frameworks, technical playbooks, reusable design patterns, and implementation guidance.
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• Participate in and lead architecture review boards, design reviews, and technical governance forums.
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• Establish COE operating practices, including governance procedures, architecture reviews, technical training, and standards adoption.
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• Develop measurable indicators for architecture standards adoption, COE effectiveness, and AI technology adoption.
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• Collaborate with technology leadership to promote architectural consistency and enterprise-wide reuse.
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• Provide architectural guidance and mentorship to application developers, engineering teams, and solution architects.
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Cloud Architecture & Application Modernization

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• Design modern, scalable, secure enterprise application architectures across Microsoft Azure, Amazon Web Services (AWS), and hybrid cloud environments.
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• Guide modernization of legacy enterprise applications using cloud-native design principles and integration patterns.
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• Define application architecture approaches supporting scalability, reliability, interoperability, and maintainability.
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• Evaluate cloud architecture options and recommend appropriate technologies based on enterprise requirements.
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• Collaborate with engineering and DevOps teams to ensure architecture standards are reflected in implementation and deployment practices.
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• Support technical design decisions throughout application modernization and cloud transformation initiatives.
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Security, Compliance & Responsible AI

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• Ensure application, integration, and AI architectures align with enterprise cybersecurity policies and security requirements.
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• Incorporate security controls consistent with NIST, NIST AI Risk Management Framework (AI RMF), CIS, and ISO 27001.
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• Define secure architecture patterns for AI agents, APIs, application integrations, and cloud services.
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• Establish appropriate controls for AI identity, authorization, audit logging, monitoring, and human oversight.
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• Collaborate with cybersecurity teams to identify architecture risks and develop mitigation strategies.
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• Promote secure-by-design principles across enterprise application and AI initiatives.
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• Technical Leadership & Stakeholder Engagement
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• Serve as a senior technical advisor on enterprise application architecture, AI integration, cloud modernization, and architectural governance.
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• Partner with product management, engineering, DevOps, cybersecurity, and enterprise architecture teams.
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• Lead technical discussions and architecture reviews involving complex enterprise applications and integrations.
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• Present architectural recommendations, standards, technical trade-offs, and implementation approaches to senior technology leaders and business stakeholders.
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• Translate enterprise technology objectives into actionable architecture strategies and reference designs.
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• Drive consistency in architectural decisions across teams, projects, and technology platforms.
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Qualifications

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• 10+ years of experience in application architecture, enterprise architecture, solution architecture, or closely related technical roles.
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• Extensive experience designing enterprise applications and cloud-native solutions using Azure and/or AWS.
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• Demonstrated experience delivering AI, LLM-based, or Agentic AI solutions in enterprise environments.
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• Strong understanding of multi-agent orchestration, RAG architectures, tool calling, and AI integration patterns.
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• Experience designing secure integration patterns for AI agents and enterprise applications.
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• Advanced knowledge of enterprise integration architecture, API design, API lifecycle management, messaging, and event-driven systems.
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• Experience defining and publishing enterprise application architecture standards, integration standards, and reference architectures.
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• Experience establishing, supporting, or operating an Architecture Center of Excellence, architecture review board, or enterprise architecture governance function.
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• Strong understanding of cloud architecture, application modernization, and hybrid integration patterns.
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• Familiarity with enterprise security standards and frameworks, including NIST, CIS, and ISO 27001.
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• Demonstrated ability to lead complex architecture initiatives and provide technical guidance across multiple engineering teams.
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• Excellent written and verbal communication skills, including the ability to present complex technical concepts to executive-level stakeholders.
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• Strong analytical, problem-solving, architectural documentation, and stakeholder management capabilities.
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Critical Technical Experience

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The following experience is particularly important:

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• IT Architecture: 6+ years
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• Information Architecture: 6+ years
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• Developing Complex Data Architectures: 6+ years
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• Computer Systems Architecture: 4–6 years preferred
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• Enterprise Application Architecture: 10+ years overall
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• Agentic AI / LLM Solutions: Demonstrated enterprise delivery experience
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• Integration & API Architecture: Strong hands-on design and governance experience
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• Architecture COE / Governance: Demonstrated standards development and architecture review experience
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Preferred Qualifications

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• Cloud certifications in Microsoft Azure, AWS, or related enterprise architecture technologies.
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• Additional relevant enterprise architecture, integration, AI, or security certifications.
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• Experience establishing architecture governance processes and enterprisewide technical standards.
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• Experience developing reusable AI architecture patterns and secure agentic AI frameworks.
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• Familiarity with MCP, multi-agent orchestration, RAG, and human-in-the loop architectures.
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• Experience defining architecture adoption metrics and supporting enterprise AI adoption initiatives.
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• Experience supporting large, complex, highly regulated or public-sector organizations.
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• Experience working with enterprise modernization programs involving legacy, SaaS, cloud-native, and hybrid systems.
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Key Technologies & Areas of Expertise

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• Enterprise Application Architecture
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• Enterprise / Solution Architecture
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• Agentic AI / AI Agents
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• Generative AI / Large Language Models (LLMs)
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• Multi-Agent Orchestration
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• Retrieval-Augmented Generation (RAG)
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• Model Context Protocol (MCP)
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• AI Tool Calling
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• Human-in-the-Loop Controls
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• AI Security, Governance & Observability
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• Enterprise Integration Architecture
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• API-Led Integration / API Gateways
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• REST APIs / API Lifecycle Management
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• Event-Driven Architecture
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• Messaging & Enterprise Integration Patterns
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• Microsoft Azure / AWS
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• Hybrid Cloud Architecture
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• Cloud-Native Application Design
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• Application Modernization
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• Architecture Center of Excellence (COE)
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• Architecture Review Boards
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• Reference Architecture & Standards Development
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• Information & Data Architecture
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• NIST AI RMF / CIS / ISO 27001
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• Technical Leadership & Architecture Governance
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