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C
Cognizant
GenAI Architect
Career Insights for Enterprise Architect
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Based on Ohio data
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What they do
An Enterprise Architect is responsible for ensuring that the business mission, strategy, and processes of an organization are aligned with the organization's IT strategy, and documents this using multiple architectural models or views that show how best to meet the current and future needs of the organization.
$145,833 / year median in Ohio
+8% projected growth
Job Description
GenAI Architect Cognizant - 3.8 Brooklyn, OH Job Details Full-time $130,000 - $155,000 a year 3 hours ago Benefits Paid parental leave Employee stock purchase plan Paid holidays Disability insurance Health insurance Dental insurance 401(k) Paid time off Parental leave Vision insurance Life insurance Qualifications AI models Containerization systems Performance tuning Software engineering Privacy law compliance Continuous Delivery (CD) implementation Team leadership Enterprise software System performance optimization Software implementation Generative models Enterprise solutions implementation AI platforms (beyond public GPTs) Security compliance frameworks implementation Enterprise software systems development Prompt engineering Databases Microservices Information security compliance Technical solutions implementation Event-driven architecture Programming languages Machine learning cloud services Machine intelligence Model deployment Developing large-scale AI models Regulatory Frameworks (Architecture security) Cloud Native Design APIs Cloud compliance Full Job Description About the role: As a GenAI Architect , you will make an impact by designing and delivering enterprise-scale Generative AI solutions that drive innovation across business and technology platforms. You will be a valued member of the AI and Engineering team and work collaboratively with product leaders, data scientists, engineers, enterprise architects, and key business stakeholders to develop scalable, secure, and responsible AI solutions. In this role, you will: Design and own end-to-end architecture for Generative AI powered products and platforms. Lead the implementation of scalable AI solutions utilizing large language models (LLMs), multimodal models, RAG frameworks, and agent-based architectures. Establish architecture standards, patterns, and best practices for prompt engineering, model orchestration, inference optimization, and AI governance. Partner with product and engineering teams to translate business requirements into AI-enabled capabilities and technical solutions. Ensure all AI solutions align with security, compliance, privacy, and responsible AI standards while delivering business value.