Enterprise AI Architect

Role Overview

Software Guidance & Assistance, Inc., (SGA), is searching for an ENTERPRISE AI ARCHITECT for a CONTRACT assignment with one of our premier INSURANCE clients in HARTFORD, CT OR CHARLOTTE NC
.

This is a Hybrid role - 3 days in office (Charlotte or Hartford - No remote option).

We are seeking a highly skilled, hands‑on AI Architect to support the Enterprise Technology Architecture (ETA) organization. This role will be responsible for leading the design, governance, and implementation of AI‑centric technology architectures across a hybrid infrastructure landscape, including AWS, Google Cloud Platform, and on‑premises data centers.

The AI Architect will play a critical role in enabling the responsible and secure adoption of Generative AI (GenAI) technologies, establishing architectural standards, and driving the implementation of multiple internal‑facing GenAI use cases. This role requires a strong blend of strategic architectural background and hands‑on technical execution.

• Architecture & Strategy:
  Design and develop Agentic AI solutions leveraging Google ADK, Lang Graph/Langchain and Agent Engine on Google Cloud Platform; deliver innovative AI capabilities that enhance business processes and customer experiences through GenAI and Agentic AI frameworks; ensure AI solutions align with enterprise technology strategy and meet scalability, security, and compliance requirements; drive adoption of GenAI and Agentic AI frameworks across business units;
  
  conduct proof‑of‑concepts (POCs) for emerging AI technologies and frameworks; collaborate with enterprise architects to ensure AI solutions align with technology strategy and reference architectures; stay current with AI trends, frameworks, and best practices to propose innovative solutions.
• Cloud Security (AWS & Google Cloud Platform):
  Architect and implement secure cloud solutions leveraging native services and third‑party tools; define and enforce cloud security posture management (CSPM), identity and access management (IAM), and encryption strategies; collaborate with Dev Ops and cloud engineering teams to embed security into CI/CD pipelines and infrastructure‑as‑code.
• Datacenter & Hybrid Security:
  Ensure secure integration between cloud platforms and on‑prem datacenters, including network segmentation, VPNs, and secure data flows; oversee security controls for legacy systems and their modernization paths.
• GenAI Security Enablement:
  Define security and governance frameworks for GenAI platforms and use cases; ensure responsible AI practices including data privacy, model integrity, and ethical AI usage; collaborate with AI/ML teams to secure model training, inference, and deployment pipelines.
• Governance &
  
  Collaboration:
  
  Serve as a key member of the Enterprise Technology & Solution Governance; partner with business, IT, and risk stakeholders to align security architecture with enterprise goals; provide technical guidance and mentorship to junior engineers and architects on AI development practices.

• Experience:
  
  10‑12 years in Software Engineering, with at least 2+ years in GenAI and Agentic AI development.
• Project Delivery:
  Must have delivered at least one GenAI or Agentic AI project end‑to‑end.
• Technical Expertise:
  Strong proficiency in Google ADK, Lang Graph/Langchain, Agent Engine, and Vertex AI; hands‑on experience with Google Cloud Platform services:
  Cloud Run, ECS, Vertex AI Search Engine, IAM, and networking; solid understanding of GenAI patterns, LLM fine‑tuning, and prompt engineering.
• Programming
  
  Skills:
  
  Python, Java, or similar languages for AI development.
• Cloud
  
  Certifications:
  
  Google Cloud Platform Professional Machine Learning Engineer or Google Cloud Platform Professional Cloud Architect preferred.
• Education:
  
  Bachelor's or Master's degree in Computer Science, AI/ML, or related field.
• Soft Skills:
  
  Strong problem‑solving, communication, and collaboration skills.

• Strategic and analytical thinking.
• Successfully integrated AI agents into business or technical workflows for automation and enhanced decision‑making.
• Improved operational efficiency and customer experience through AI‑driven…