Enterprise Architect

PERENNIAL RESOURCES INTL LLC
Charlotte, NC, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
10 years minimum
Working hours
Regular working hours
Job source

Tech stack

Java (Programming Language) Artificial Intelligence Amazon Web Services Amazon S3 Architectural Patterns Microsoft Azure C Sharp (Programming Language) Software as a Service Cloud Engineering Data Architecture Disaster Recovery Amazon DynamoDB
+22 more
Enterprise Architecture Framework Identity and Access Management Python (Programming Language) Node.Js Software Architecture Software Engineering Enterprise Application Integration Google Cloud Enterprise Software Applications Retrieval-Augmented Generation Large Language Models State Machines Event Driven Architecture Amazon Relational Database Service AI Platforms Kubernetes Data Analytics Data Management Api Design Api Gateway Serverless Computing Docker

Job description

We are seeking an experienced Senior Enterprise Architect to join our Client’s Architecture team. This is a senior technical leadership role responsible for defining and governing enterprise-wide architecture across applications, platforms, data, cloud, and emerging technologies, with AI and agentic automation as key enabling capabilities.

The role focuses on setting direction, standards, and guardrails to ensure scalable, secure, and well-governed solutions across the organization.

Responsibilities

Enterprise Architecture & Strategy:

  • Define and maintain enterprise architecture across application, data, integration, cloud, and platform domains
  • Lead the design and implementation of scalable cloud-native solutions and establish architecture standards based on practical delivery experience.
  • Ensure consistent adoption of enterprise patterns across technology initiatives
  • Integrate AI, automation, and analytics capabilities into the broader enterprise architecture
  • Align technology architecture with business strategy and long-term roadmap

Technical Leadership:

  • Provide architectural leadership across major enterprise initiatives
  • Guide solution architects and engineering teams on architecture decisions
  • Define reusable architectural patterns and shared platform capabilities
  • Act as a design authority for complex, cross-domain solutions
  • Balance innovation with stability, security, and operational maturity

Standards & Governance:

  • Establish governance models for platforms, integrations, data, and AI-enabled solutions
  • Define security, compliance, and risk guardrails in collaboration with security and risk teams
  • Review solution designs for alignment with enterprise standards
  • Ensure architectural consistency across cloud, SaaS, and on-prem solutions
  • Promote observability, resiliency, disaster recovery, and operational readiness by design

Solution Design & Review:

  • Review and approve AI solution designs
  • Ensure alignment with enterprise architecture standards
  • Identify opportunities for reusable components
  • Guide teams on technical implementation approaches
  • Evaluate new AI technologies and platforms

Emerging Technology & Platform Evolution:

  • Drive the evolution of Client’s AI platform capabilities
  • Evaluate emerging technologies including AI/GenAI, automation, and data platforms
  • Define how AI capabilities are responsibly embedded into enterprise solutions.
  • Define roadmap for platform capabilities and features
  • Guide integration with existing enterprise systems

Requirements

  • You must have 10+ years in software engineering, solution architecture, or enterprise architecture.
  • Demonstrated hands-on experience designing, building, deploying, and supporting enterprise solutions on AWS, including the ability to explain architectural decisions, trade-offs, scalability, security, and operational considerations.
  • Strong background in large-scale, distributed enterprise systems
  • Proven experience designing cloud-native and hybrid architectures
  • Hands-on understanding of data, integration, and platform architectures
  • Experience incorporating AI and automation into enterprise solutions (not limited to AI platforms)
  • Experience owning and delivering complex enterprise applications end-to-end, including architecture, development, deployment, support, and continuous improvement
  • Experience designing highly available, scalable, and disaster recovery-enabled solutions.
  • Ability to explain solution architecture and technical decisions end to end

You should possess the following skills:

  • Strong enterprise architecture frameworks, principles, and governance experience
  • This is a hands-on architecture role. Candidates must have recent experience building and implementing enterprise applications and be comfortable reviewing code, solution designs, and technical implementations.
  • Deep expertise in application, data, integration, and cloud architecture
  • Strong software engineering background with hands-on development experience. Experience with Python, Node.js, Java, C#, or similar languages is acceptable, provided candidates can demonstrate ownership of application design and implementation. xrbllit
  • Extensive hands-on experience with AWS services and cloud-native design patterns (compute, storage, networking, serverless, IAM, etc.)
  • Strong understanding of security, compliance, and risk considerations
  • Experience with API-driven and event-driven architectures
  • Data architecture, governance, and integration patterns
  • Ability to translate strategy into executable architecture
  • Clear technical communication with senior stakeholders

Technical Expertise:

  • AWS cloud platform (e.g., Lambda, ECS/EKS, S3, DynamoDB, RDS, API Gateway, Step Functions, IAM)
  • Strong understanding of production operations, observability, reliability, and operational support models
  • Kubernetes
  • Docker
  • Container orchestration platforms
  • Cloud-native deployment architectures
  • Development using Python and/or Node.js
  • Large Language Models and GenAI technologies
  • RAG architectures and implementation patterns
  • Cloud AI services (AWS, Azure, GCP)
  • Enterprise integration patterns
  • Security and compliance frameworks
  • Data architecture and governance

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