AI Engineer
Posted 17 days ago
You'll complete your application on Pear Tree.'s career site.
About the Role
This role involves serving as an AI Engineer who connects complex business challenges with advanced technical AI implementations. You will partner with the founder and client stakeholders across the full project lifecycle, managing tasks from early feasibility assessments to final delivery. The position entails working in a client-facing capacity, where you will convert business needs into technical specifications and provide training and documentation to support clients. Your primary focus will be developing custom AI applications, architecting solutions with both standard and specialized models, and integrating Large Language Models and agentic workflows into existing client infrastructure while maintaining high standards for security, cost-efficiency, and performance across logistics, consulting, and marketing sectors.
Requirements
- Minimum of 5 years in professional software engineering, with at least 2 years focused on developing AI applications for production.
- A degree in physics, mathematics, engineering, or computer science, or equivalent industry experience.
- Advanced Python skills with a focus on writing maintainable, well-tested, and packaged code.
- Significant experience with LLM integration, including evaluation, prompt design, and RAG, alongside building agents with tools like the Model Context Protocol.
- Proficiency in SQL and the creation of data pipelines.
- Practical experience deploying and training machine learning models using libraries such as XGBoost, scikit-learn, or PyTorch.
- Demonstrated experience with AWS or Azure cloud deployments.
- Ability to explain technical trade-offs to stakeholders without a technical background.
Responsibilities
- Design architectural solutions utilizing RAG, agentic frameworks, and custom models tailored to specific client requirements and budgets.
- Integrate Large Language Models into client environments by focusing on prompt engineering, tool utilization, and autonomous workflows.
- Oversee the validation, training, and deployment of machine learning models for applications like demand forecasting and anomaly detection.
- Examine client data to determine project feasibility and construct the requisite data pipelines.
- Maintain production systems by tracking latency, model drift, and accuracy while implementing security measures to prevent prompt injection and data leaks.
- Work with executive leadership to define technical requirements from business challenges, present project proposals, and train client staff on system maintenance.
Benefits & Perks
- You will operate according to Australian holidays and Australian business hours.
Note: This listing is summarized and paraphrased by WorkNow from a publicly posted role. For the original wording and full details, please refer to the employer's official posting.
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