AI Engineer

This is a fully remote position, open to applicants in Philippines.

📋 Description

• Develop solution architecture utilizing off-the-shelf models, RAG, agents, and tailored models based on client requirements and budgets.

• Incorporate LLMs into client systems, focusing on prompt design, tool utilization, and agentic workflows.

• Train, validate, and implement machine learning models for demand forecasting, anomaly detection, and related challenges.

• Analyze client data to evaluate use-case feasibility and construct supporting data pipelines.

• Assess and monitor production solutions for accuracy, drift, latency, and cost, making optimizations as necessary.

• Write secure, tested code with protections against prompt injection and data leakage.

• Collaborate with client executives, business users, and IT teams to convert business challenges into technical specifications and contribute to proposals.

• Deliver solutions with comprehensive documentation and training to enable client teams to operate and maintain them.

• Partner directly with the founder and client teams from project scoping through to go-live and handover.

⛳️ Requirements

• Over 5 years of professional software engineering, including a minimum of two years focused on developing AI applications in production environments.

• Experience in consulting or professional services, delivering results to external clients within a defined scope.

• A bachelor's or master's degree in computer science, engineering, mathematics, or physics, or equivalent hands-on experience.

• Proficient in advanced Python, including testing, packaging, and writing maintainable code for other engineers.

• Regular use of AI engineering tools like Claude Code or Codex, including reviewing, testing, and refining generated code.

• Practical experience in integrating LLMs into applications, covering RAG, prompt design, tool usage, and evaluation.

• Familiarity with building agents using the Model Context Protocol (MCP) or other agent frameworks.

• Experience in training and deploying machine learning models using libraries such as scikit-learn, PyTorch, or XGBoost.

• Strong SQL skills and experience in constructing data pipelines.

• Experience deploying solutions on at least one cloud platform, ideally Azure or AWS, utilizing containers and CI/CD practices.

• Ability to articulate technical trade-offs to non-technical executives in clear, understandable terms.

• Desired (not mandatory): Familiarity with data platforms like Databricks, Snowflake, or Microsoft Fabric, and transformation tools like dbt.

• Desired (not mandatory): Knowledge of LLM evaluation and observability tools such as MLflow, Langfuse, or LangSmith.

• Desired (not mandatory): Understanding of LLM security risks, particularly those outlined in the OWASP Top 10 for LLM Applications.

• Desired (not mandatory): Experience conducting training sessions or workshops for both technical and business audiences.

🏝️ Benefits

• Adherence to Australian working hours.

• Recognition of Australian holidays.