Gen AI Developer
Cognizant Technology Solutions Corporation
Charlotte, NC, United States
about 1 month ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source
Tech stack
Application Programming Interfaces (APIs)
Artificial Intelligence
Amazon Web Services
Software Applications
Cloud Computing
Cloud Engineering
Continuous Integration
DevOps
Distributed Systems
Software Architecture
Spring Cloud
GitHub Copilot
+13 more
Large Language Models
Prompt Engineering
IT Architecture
Generative AI
Agentic-AI
Build Management
AI Platforms
Kubernetes
Amazon Bedrock
Claude
Google Gemini
GPT
Microservices
Job description
- Lead the architecture, design, and implementation of enterprise Generative AI solutions across business and technology programs.
- Design scalable, cloud-native architectures leveraging Large Language Models (LLMs), AI agents, APIs, orchestration frameworks, and microservices.
- Build and deploy AI-powered applications using technologies such as GPT, Claude, Gemini, Llama, and advanced Prompt and Context Engineering techniques.
- Drive AI-assisted software engineering practices using tools such as GitHub Copilot and other AI development solutions to improve engineering productivity and accelerate delivery.
- Architect and implement solutions leveraging AWS, Amazon Bedrock, and modern cloud technologies.
- Establish best practices for AI platform engineering, responsible AI adoption, DevOps, and CI/CD automation.
- Collaborate with stakeholders to define AI strategies, solution roadmaps, and implementation approaches.
- Provide technical leadership and mentor engineering teams on AI architecture, platform engineering, and cloud-native development.
Requirements
- Proven experience designing and delivering Generative AI solutions in enterprise environments.
- Strong expertise in LLMs, AI Agents, Prompt Engineering, and Context Engineering.
- Experience building cloud-native applications using AWS, including AI and platform services.
- Experience with AI-assisted development tools such as GitHub Copilot, Claude, or similar technologies.
- Strong understanding of APIs, microservices, distributed systems, and modern software architecture patterns.
- Experience with DevOps, CI/CD pipelines, and engineering automation practices.
- Strong stakeholder management, communication, and leadership skills.
- Experience leading architecture discussions and influencing enterprise technology strategy.
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