Artificial Intelligence Engineer
2 days ago
Job Description:
- We are seeking a versatile and innovative AI Engineer to join our team in building intelligent, GPT-powered applications and systems.
- This role involves designing and implementing AI-driven solutions across the stackfrom model integration and data processing to user-facing features.
- The ideal candidate is passionate about artificial intelligence, has hands-on experience with modern AI tools and platforms, and thrives in a collaborative, fast-paced environment.
Key Responsibilities:
- Design, develop, and deploy AI-powered applications using GPT models and other LLMs.
- Integrate AI capabilities into web and backend systems using APIs and custom workflows.
- Implement document vectorisation and AI search pipelines for intelligent retrieval and automation.
- Collaborate with cross-functional teams (product, engineering, data science) to define and deliver AI features.
- Optimize models and applications for performance, scalability, and reliability.
- Develop and maintain Python-based scripts and services for data processing and model interaction.
- Work with cloud platforms (especially Microsoft Azure) to deploy and manage AI services.
- Stay current with advancements in AI/ML, LLMs, and emerging technologies.
- Participate in code reviews, architecture discussions, and mentoring activities.
Skills and Qualifications:
- Strong proficiency in Python, with experience in AI/ML development. Familiarity with GPT APIs (e.g., OpenAI, Azure OpenAI) and prompt engineering.
- Experience integrating AI search and document vectorisation techniques.
- Solid understanding of RESTful APIs, asynchronous workflows, and data pipelines.
- Hands-on experience with Microsoft Azure, especially in deploying AI services.
- Proficiency with Git basics and modern CI/CD workflows.
- Strong problem-solving skills and attention to detail.
- Excellent communication and collaboration abilities.
Preferred Qualifications:
- Experience working on AI/ML products or in data-driven environments.
- Familiarity with SAFe or other agile methodologies.
- Exposure to backend technologies (e.g., , Express) or cloud platforms like AWS, Vercel.
- Understanding of model fine-tuning, evaluation metrics, and deployment strategies.
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