
Intelligent Systems Engineer
24 hours ago
A key objective of this role is to create, develop, and integrate large language models (LLMs) with artificial intelligence (AI) agents.
You will be responsible for designing and optimizing prompt engineering workflows for LLMs. This may involve working with GPT, Claude, or LLaMA models.
In addition, you will develop modular, reusable components for agent orchestration and task automation.
In the Model Deployment & Infrastructure section, you will deploy models using Databricks and Azure ML, integrating with enterprise-grade systems. You will also implement APIs, WebSockets, and event-driven architectures for real-time AI services.
This position requires collaboration with platform teams to ensure scalable and secure deployments.
Within the Development & Automation section, you will work with CI/CD pipelines using Jenkins to automate testing and deployment. You will use tools such as GitHub Copilot, Windsurf, Codeium, or similar tools to accelerate development.
Maintaining high code quality and documentation standards using Git, Jira, and Confluence will also be an important part of this job.
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