Enterprise AI Engineer: LLMs, Pipelines & Production

Pear Tree.; Philippines; Remote; PHP 1,219,000 - 1,460,000; Full time

Job summary

Pear Tree. is seeking an AI Engineer to build and deploy production‑grade AI/ML solutions for enterprise clients in Australia.

You will translate client problems into scalable systems, covering LLMs, ML models, and data pipelines, with direct collaboration from the founder and client teams through go‑live and handover. The role emphasizes producing robust, maintainable code, delivering to external clients with a focus on accuracy, speed, and cost management.

Qualifications

• 5+ years of professional software engineering, with 2+ years in AI in production.
• Consulting or services experience delivering work to external clients.
• Bachelor’s or Master’s in CS/engineering/math/physics or equivalent.
• Advanced Python, testing and maintainable code.
• Experience integrating LLMs into applications (RAG, prompts, tools).
• Experience deploying ML models with libraries like scikit-learn, PyTorch or XGBoost.
• Strong SQL and data pipelines; cloud deployment with CI/CD.

Responsibilities

• Design architecture selecting models, RAG, agents or custom solutions per client.
• Integrate LLMs into client systems, with prompts and tool usage.
• Train, validate and deploy ML models for demand forecasting or anomaly detection.
• Analyze client data and build data pipelines feeding models.
• Monitor production solutions for accuracy, drift, latency and cost.
• Write secure, tested code with guardrails against prompts leakage.
• Translate business problems into technical requirements for proposals.
• Hand over solutions with documentation and client training.

Skills

Python

AI applications

SQL

Data pipelines

Cloud platforms

CI/CD

Explain trade-offs

Education

Bachelor's or Master's in CS/Engineering/Math/Physics

Tools

Claude Code

Codex

scikit-learn

PyTorch

XGBoost

Job description

Pear Tree. is seeking an AI Engineer to build and deploy production‑grade AI/ML solutions for enterprise clients in Australia.

You will translate client problems into scalable systems, covering LLMs, ML models, and data pipelines, with direct collaboration from the founder and client teams through go‑live and handover. The role emphasizes producing robust, maintainable code, delivering to external clients with a focus on accuracy, speed, and cost management.