GenAI Architect – Enterprise AI Solutions Leader

Cognizant Technology Solutions Corporation; Charlotte (NC); Hybrid; USD 100,000 - 150,000; Full time

Benefits offered by this job

Medical/Dental/Vision/Life Insurance

Paid holidays plus Paid Time Off

401(k) plan and contributions

Long-term/Short-term Disability

Paid Parental Leave

Employee Stock Purchase Plan

Job summary

Cognizant Technology Solutions Corporation in Charlotte, NC is seeking a GenAI and Agentic AI Solutions Architect to design, architect, and develop enterprise-grade Generative AI solutions that accelerate AI-first transformation.

You will build scalable AI applications, copilots, intelligent agents, and reusable accelerators using large language models and agent orchestration frameworks, with RAG, vector databases, and prompt engineering.

Qualifications

• Proven experience designing and building production-grade Generative AI solutions.
• Strong background in solution architecture and cloud-native development.
• Hands-on software engineering with AI-assisted tooling in enterprise settings.

Responsibilities

• Lead architecture, design, and hands-on development of enterprise Generative AI solutions.
• Architect scalable AI applications, copilots, and intelligent agents with modern LLMs.
• Implement RAG, vector stores, prompt/context engineering for enterprise use cases.
• Promote reusable AI patterns, CI/CD, and cloud-native architectural standards.
• Collaborate with teams to accelerate delivery using AI-assisted engineering tools.

Skills

Generative AI

Agentic AI

Solution architecture

Cloud-native development

Hands-on development

Tools

AWS Bedrock

GitHub Copilot

Claude Code

Vector databases

Agent orchestration frameworks

Job description

Cognizant Technology Solutions Corporation in Charlotte, NC is seeking a GenAI and Agentic AI Solutions Architect to design, architect, and develop enterprise-grade Generative AI solutions that accelerate AI-first transformation.

You will build scalable AI applications, copilots, intelligent agents, and reusable accelerators using large language models and agent orchestration frameworks, with RAG, vector databases, and prompt engineering.