GenAI/Agentic AI Architect

Cognizant

Confirmed live today High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Charlotte, NC
Salary: $116,100–$180,000 / yr
Posted: 8 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $216k

This role $148k

$99k $277k

below market most similar roles pay here above market

This role pays less than 91% of similar roles. Most pay $184,975–$247,487 — the blue band above. At the midpoint, this role pays about $148k versus about $216k for comparable roles.

Based on 240 similar postings.

Employer

About Cognizant

Cognizant is a multinational IT services and consulting company offering digital transformation, technology, and business process services. It serves clients across financial services, healthcare, manufacturing, and other industries worldwide.

Cognizant currently has 397 open roles on FindRole.

Listed pay typically runs $100,000–$135,000 across 262 roles with salary data.

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At a glance

TL;DR · GenAI/Agentic AI Architect

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As a GenAI/Agentic AI Architect, you will join the engineering and architecture teams to lead the design and hands-on development of enterprise-grade Generative AI and Agentic AI solutions. You will build scalable AI applications, copilots, intelligent agents, and reusable accelerators to drive AI-first transformation. Your daily work involves architecting solutions using Retrieval-Augmented Generation, vector databases, prompt engineering, and context engineering to solve complex enterprise use cases. You will utilize modern large language models including GPT, Claude, Gemini, and Llama, alongside AWS Bedrock and agent orchestration frameworks. Additionally, you will employ AI-assisted engineering tools like GitHub Copilot and Claude Code while establishing reusable patterns that support cloud-native architecture, CI/CD practices, and enterprise software engineering standards across complex technology environments.

Skills

Generative AI Agentic AI LLMs RAG AWS Bedrock Vector Databases Prompt Engineering Context Engineering GitHub Copilot Claude Code CI/CD Cloud-Native Architecture GPT Claude Gemini Llama Agent Orchestration Frameworks

What you'll do

Lead the architecture, design, and hands-on development of enterprise-grade Generative AI and Agentic AI solutions.
Build scalable AI applications, copilots, intelligent agents, and reusable accelerators using modern LLMs and orchestration frameworks.
Design solutions leveraging Retrieval-Augmented Generation (RAG), vector databases, prompt engineering, and context engineering.
Utilize AWS Bedrock and other cloud-native technologies to develop production-grade AI systems.
Establish reusable AI engineering patterns and utilities that support CI/CD practices and enterprise software standards.
Integrate Generative AI capabilities into existing enterprise platforms, applications, and engineering workflows.
Evaluate and select appropriate LLMs and agent frameworks based on specific enterprise use cases.

What we're looking for

18+ years of overall technology experience with expertise in software engineering, solution architecture, and cloud-native application development.
Proven experience designing and building production-grade Generative AI solutions using LLMs such as GPT, Claude, Gemini, or Llama.
Strong experience with Agentic AI, agent orchestration frameworks, Retrieval-Augmented Generation (RAG), vector databases, prompt engineering, and context engineering.
Hands-on experience architecting and developing cloud-based AI solutions, including AWS Bedrock and modern cloud-native architecture patterns.
Strong software engineering expertise applying AI-assisted development and CI/CD practices to enterprise software delivery.
Hands-on experience using GitHub Copilot, Claude Code, or similar AI-assisted development tools to improve engineering productivity (preferred).
Experience developing reusable GenAI accelerators, frameworks, utilities, or developer tooling for enterprise environments (preferred).
Experience evaluating LLMs, agent frameworks, and AI architecture patterns or leading AI-first transformation initiatives (preferred).

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