AI Engineer
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Summary
Builds and deploys AI agents and agentic AI-powered applications for enterprise and ERP use cases, integrating them into existing systems and maintaining them in production. Day-to-day work centers on Python (with some Node.js), LLM technologies, and AI orchestration frameworks.
- Design, develop and deploy AI agents and AI-powered applications for enterprise and ERP use cases.
- Build practical agentic AI workflows using suitable orchestration frameworks.
- Research and evaluate emerging AI technologies, frameworks and approaches to identify solutions for new use cases.
- Develop and integrate AI capabilities into existing enterprise applications and systems.
- Work with Python and, where required, Node.js to develop AI applications and integrations.
- Design AI workflows that can interact with enterprise systems, data and business processes.
- Develop, test, troubleshoot and optimize AI solutions for production environments.
- Collaborate with AI Engineers, Senior Engineers and other technical teams to integrate AI capabilities into the existing architecture.
- Deploy and maintain AI solutions in real-world production or client environments.
- Troubleshoot technical issues and continuously improve the reliability, performance and scalability of AI applications.
- Translate business and client requirements into practical AI-driven solutions.
- Stay up to date with developments in AI agents, LLM technologies, orchestration frameworks and AI application development.
Requirements
- 2–3 years of relevant experience in AI/ML Engineering, AI Application Development or a closely related field.
- Candidates with stronger or more extensive experience are also encouraged to apply.
- Strong hands-on experience developing AI applications or AI agents.
- Practical experience taking AI solutions from development through to production deployment.
- Strong Python programming skills.
- Experience integrating AI solutions with existing applications, APIs, databases or enterprise systems.
- Strong problem-solving and troubleshooting capabilities.
- Ability to independently research new technologies and learn unfamiliar tools or frameworks.
- Strong adaptability and willingness to work with emerging technologies and new AI use cases.
- Ability to explain and demonstrate AI projects that you have personally developed and implemented.