AI Architect (GenAI & Agentic AI

Charlotte, United States | Posted on 08/04/2026

• CoE/Practice Architecture, Delivery & Leadership
• City Charlotte
• State/Province North Carolina
• Country United States

Status Neo is a global AI-native transformation firm helping enterprises design, engineer, and govern AI-led systems with trust at the core.

We work with global enterprises across BFSI, retail, healthcare, airlines, and platform-driven industries to transform how software is built, operated, and scaled in an AI-first world.

Our work is anchored in Authentic AI — an approach that treats AI not as a feature or experiment, but as a continuously evolving system that must be engineered with intent, accountability, and governance.

At Status Neo, we don’t just talk about AI transformation.

We build it — across engineering platforms, AI-native SDLC, agentic systems, and enterprise operating models.

We are seeking an experienced AI Architect to lead the design and delivery of enterprise-grade AI solutions.

This role is ideal for someone who combines deep expertise in Generative AI,cloud-native architectures, and enterprise software engineering with the ability to translate business challenges into scalable AI platforms.

You will work closely with business stakeholders, enterprise architects, and engineering teams to defineAI strategy, architect intelligent systems, and drive the successful implementation of AI-powered applications across the enterprise.

• Lead the architecture and designof enterprise AI and Generative AI solutions.
• Design scalable AI platformsleveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG),AI Agents, and modern cloud services.
• Develop AI reference architectures, reusable frameworks, and engineering best practices.
• Partner with business and technology stakeholders to identify AI use cases and define implementationroadmaps.
• Guide engineering teams through architecture reviews, technical decision-making, and solution delivery.
• Design secure, scalableintegrations with enterprise applications, APIs, and data platforms.
• Establish AI governance,observability, security, and responsible AI practices.
• Mentor engineering teams and drivetechnical excellence across AI initiatives.
• Stay current with emerging AI technologies and evaluate their applicability to enterprise use cases.

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 10+ years of software engineering,solution architecture, or enterprise architecture experience.
• 3+ years designing and delivering
  
  Generative AI or Machine Learning solutions in production.
• Strong experience designing cloud-native architectures on Azure, AWS, or GCP.
• Hands-on experience with Large Language Models (OpenAI, Azure OpenAI, Anthropic, Gemini, etc.).
• Experience implementing
  
  Retrieval-Augmented Generation (RAG), vector databases, semantic search, andprompt engineering.
• Strong programming experience in Python and modern API development frameworks.
• Experience with containerization,Kubernetes, CI/CD, Infrastructure as Code, and modern Dev Ops practices.
• Strong understanding of distributed systems, APIs, microservices, and enterprise integration patterns.

• Experience with AI Agentframeworks such as Lang Graph, CrewAI, Auto Gen, Semantic Kernel, or similar.
• Experience building enterprise knowledge platforms and AI-enabled search solutions.
• Exposure to MLOps, LLMOps, AIobservability, and model lifecycle management.
• Experience integrating AI solutions with enterprise platforms such as Service Now, Git Hub, Jira, cloud infrastructure, or ITSM tools.
• Experience working within highly regulated industries such as Financial Services, Insurance, Healthcare, or Telecommunications.

• Python
• Lang Chain, Lang Graph, CrewAI or equivalent frameworks
• FastAPI / REST APIs
• Git Hub Actions / Azure Dev Ops
• SQL & No
  
  SQL Databases
• Terraform or Infrastructure asCode
• Strong consulting and stakeholder management skills.
• Ability to influence technical and business leadership.
• Excellent communication and presentation skills.
• Ability to lead cross-functional engineering teams in agile environments.
• Passion for innovation, continuous learning, and solving complex business problems through AI.