Production AI Engineer: Enterprise ML & LLMs

D2B; Philippines; On-site; PHP 1,219,000 - 1,460,000; Full time

Job summary

D2B is seeking an AI Engineer in the Philippines to design, develop, and deploy production-grade AI/ML solutions for Australian enterprise clients. You will collaborate with the founder and client teams from scoping to go-live and handover, turning business problems into scalable technical systems.

You will leverage LLMs, traditional ML, data pipelines, and cloud deployment to deliver robust solutions, with responsibilities spanning architecture, integration, testing, and training for sustained

Qualifications

• Bachelor's or Master's in computer science, engineering, mathematics or physics, or equivalent practical experience.
• Advanced Python, including testing, packaging and maintainable code.
• Experience building AI applications that run in production.

Responsibilities

• Design solution architecture selecting models, RAG, agents or custom solutions based on client problem and budget.
• Integrate LLMs into client systems including prompt design and tool use.
• Train, validate and deploy ML models for problems like demand forecasting and anomaly detection.
• Analyse client data to test feasibility and build data pipelines feeding models.
• Evaluate production solutions for accuracy, drift, latency and cost; optimize as needed.
• Write secure, tested code with guardrails against prompt injection and data leakage.
• Translate business problems into technical requirements and advise client proposals.
• Hand over solutions with documentation and training for client teams.

Skills

Advanced Python

SQL

Data pipelines

LLM integration

Cloud deployment

Education

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

Tools

Azure

AWS

Docker

CI/CD

Claude/Codex

Job description

D2B is seeking an AI Engineer in the Philippines to design, develop, and deploy production-grade AI/ML solutions for Australian enterprise clients. You will collaborate with the founder and client teams from scoping to go-live and handover, turning business problems into scalable technical systems.

You will leverage LLMs, traditional ML, data pipelines, and cloud deployment to deliver robust solutions, with responsibilities spanning architecture, integration, testing, and training for sustained