Enterprise Application Architect

System Soft Technologies; New York (NY); On-site; USD 180,000 - 260,000; Full time

Job summary

System Soft Technologies seeks a Senior Enterprise Application Architect to lead Agentic AI and enterprise integration architecture across Azure, AWS, and hybrid environments. You will design reusable patterns, establish architecture standards, and support an Architecture COE with strong governance and collaboration with senior stakeholders.

The role focuses on LLM-enabled applications, multi-agent orchestration, RAG, API-led integration, and secure, scalable enterprise solutions.

Qualifications

• 10+ years of experience in application/enterprise architecture.
• Experience delivering AI, LLM-based, or Agentic AI solutions in enterprise environments.
• Strong understanding of multi-agent orchestration, RAG, tool calling, and AI integration patterns.
• Experience establishing, supporting, or operating an Architecture COE or governance function.
• Familiarity with MCP, event-driven patterns, and secure integration.

Responsibilities

• Design enterprise reference architectures for Agentic AI and LLM-based solutions.
• Architect multi-agent systems including orchestration, tool calling, and workflows.
• Define RAG patterns to integrate enterprise data with AI apps.
• Establish secure integration patterns between AI agents, apps, APIs, and external services.
• Lead architecture reviews and governance forums; mentor teams on standards.
• Guide modernization and cloud transformation initiatives across Azure, AWS, and hybrid environments.

Skills

Leadership

Strategic thinking

Communication

Problem-solving

Executive stakeholder management

Tools

Azure

AWS

Cloud-native

API design

Job description

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

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

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

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

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

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

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

Responsibilities

Agentic AI & Enterprise AI Architecture

• Design and establish enterprise reference architectures for Agentic AI, AI enabled applications, and LLM-based solutions.


• Architect multi‑agent systems involving agent orchestration, tool calling, task delegation, and coordinated workflows.


• Design and implement Retrieval‑Augmented Generation (RAG) patterns to integrate enterprise knowledge and data with AI applications.


• Establish secure integration patterns between AI agents, enterprise applications, APIs, and external services.


• Define architectural approaches for Model Context Protocol (MCP), eventdriven triggers, and agent‑to‑system communication.


• Incorporate human‑in‑the‑loop controls, approval workflows, and appropriate oversight into agentic AI solutions.


• Establish AI architecture guardrails covering identity, access management, security, auditability, observability, evaluation, and cost optimization.


• Evaluate architectural alternatives and recommend scalable, secure, maintainable AI solutions for enterprise use cases.


• Design and govern enterprise integration architectures involving REST APIs, API‑led connectivity, messaging systems, and event‑driven integration patterns.


• Define reusable integration standards supporting legacy applications, SaaS platforms, cloud‑native applications, and enterprise systems.


• Establish API lifecycle management practices, including API design, governance, versioning, security, and gateway strategies.


• Design secure and scalable integration patterns connecting applications across Azure, AWS, and hybrid environments.


• Evaluate integration technologies and architectural approaches based on performance, reliability, scalability, security, and maintainability.


• Guide engineering teams in implementing enterprise integration standards and reusable architecture patterns.

Architecture Center of Excellence (COE) & Governance

• Help establish, develop, and operate an enterprise Architecture Center of Excellence (COE).


• Define and maintain enterprise application architecture standards, integration standards, API guidelines, and AI reference architectures.


• Develop architecture governance frameworks, technical playbooks, reusable design patterns, and implementation guidance.


• Participate in and lead architecture review boards, design reviews, and technical governance forums.


• Establish COE operating practices, including governance procedures, architecture reviews, technical training, and standards adoption.


• Develop measurable indicators for architecture standards adoption, COE effectiveness, and AI technology adoption.


• Collaborate with technology leadership to promote architectural consistency and enterprise‑wide reuse.


• Provide architectural guidance and mentorship to application developers, engineering teams, and solution architects.


• Design modern, scalable, secure enterprise application architectures across Microsoft Azure, Amazon Web Services (AWS), and hybrid cloud environments.


• Guide modernization of legacy enterprise applications using cloud‑native design principles and integration patterns.


• Define application architecture approaches supporting scalability, reliability, interoperability, and maintainability.


• Evaluate cloud architecture options and recommend appropriate technologies based on enterprise requirements.


• Collaborate with engineering and DevOps teams to ensure architecture standards are reflected in implementation and deployment practices.


• Support technical design decisions throughout application modernization and cloud transformation initiatives.

Security, Compliance & Responsible AI

• Ensure application, integration, and AI architectures align with enterprise cybersecurity policies and security requirements.


• Incorporate security controls consistent with NIST, NIST AI Risk Management Framework (AI RMF), CIS, and ISO 27001.


• Define secure architecture patterns for AI agents, APIs, application integrations, and cloud services.


• Establish appropriate controls for AI identity, authorization, audit logging, monitoring, and human oversight.


• Collaborate with cybersecurity teams to identify architecture risks and develop mitigation strategies.


• Promote secure‑by‑design principles across enterprise application and AI initiatives.


• Technical Leadership & Stakeholder Engagement


• Serve as a senior technical advisor on enterprise application architecture, AI integration, cloud modernization, and architectural governance.


• Partner with product management, engineering, DevOps, cybersecurity, and enterprise architecture teams.


• Lead technical discussions and architecture reviews involving complex enterprise applications and integrations.


• Present architectural recommendations, standards, technical trade‑offs, and implementation approaches to senior technology leaders and business stakeholders.


• Translate enterprise technology objectives into actionable architecture strategies and reference designs.


• Drive consistency in architectural decisions across teams, projects, and technology platforms.

Qualifications

• 10+ years of experience in application architecture, enterprise architecture, solution architecture, or closely related technical roles.


• Extensive experience designing enterprise applications and cloud‑native solutions using Azure and/or AWS.


• Demonstrated experience delivering AI, LLM‑based, or Agentic AI solutions in enterprise environments.


• Strong understanding of multi‑agent orchestration, RAG architectures, tool calling, and AI integration patterns.


• Experience designing secure integration patterns for AI agents and enterprise applications.


• Advanced knowledge of enterprise integration architecture, API design, API lifecycle management, messaging, and event‑driven systems.


• Experience defining and publishing enterprise application architecture standards, integration standards, and reference architectures.


• Experience establishing, supporting, or operating an Architecture Center of Excellence, architecture review board, or enterprise architecture governance function.


• Strong understanding of cloud architecture, application modernization, and hybrid integration patterns.


• Familiarity with enterprise security standards and frameworks, including NIST, CIS, and ISO 27001.


• Demonstrated ability to lead complex architecture initiatives and provide technical guidance across multiple engineering teams.


• Excellent written and verbal communication skills, including the ability to present complex technical concepts to executive‑level stakeholders.


• Strong analytical, problem‑solving, architectural documentation, and stakeholder management capabilities.

Critical Technical Experience

The following experience is particularly important:

• IT Architecture: 6+ years


• Information Architecture: 6+ years


• Developing Complex Data Architectures: 6+ years


• Computer Systems Architecture: 4–6 years preferred


• Enterprise Application Architecture: 10+ years overall


• Agentic AI / LLM Solutions: Demonstrated enterprise delivery experience


• Integration & API Architecture: Strong hands‑on design and governance experience


• Architecture COE / Governance: Demonstrated standards development and architecture review experience

Preferred Qualifications

• Cloud certifications in Microsoft Azure, AWS, or related enterprise architecture technologies.


• Additional relevant enterprise architecture, integration, AI, or security certifications.


• Experience establishing architecture governance processes and enterprisewide technical standards.


• Experience developing reusable AI architecture patterns and secure agentic AI frameworks.


• Familiarity with MCP, multi‑agent orchestration, RAG, and human‑in‑the loop architectures.


• Experience defining architecture adoption metrics and supporting enterprise AI adoption initiatives.


• Experience supporting large, complex, highly regulated or public‑sector organizations.


• Experience working with enterprise modernization programs involving legacy, SaaS, cloud‑native, and hybrid systems.

Key Technologies & Areas of Expertise

• Agentic AI / AI Agents


• Multi‑Agent Orchestration


• Retrieval‑Augmented Generation (RAG)


• AI Tool Calling


• Human‑in‑the‑Loop Controls


• AI Security, Governance & Observability


• API‑Led Integration / API Gateways


• REST APIs / API Lifecycle Management


• Cloud‑Native Application Design


• Application Modernization


• Architecture Center of Excellence (COE)


• Reference Architecture & Standards Development


• NIST AI RMF / CIS / ISO 27001


• Technical Leadership & Architecture Governance