Senior AI Engineer

APW Tech; Mandaluyong; On-site; PHP 600,000 - 1,100,000; Full time

Job summary

APW Tech in Metro Manila is seeking a data-focused engineer to help design and deploy production data pipelines, automation solutions, and AI integration across systems. The ideal candidate holds a related Bachelor's degree and 2–4 years in data/platform engineering or MLOps, with hands-on experience, independent problem solving, and familiarity with Python-based data tooling and modern AI workflows.

Knowledge of LangChain, Spark, and PostgreSQL is a plus, as is experience with RAG pipelines and

Qualifications

• Bachelor's degree in a related field
• 2 to 4 years in data engineering, platform engineering, MLOps, or operations-focused technical role
• Hands-on experience building automation solutions or data pipelines in production
• Exposure to AI/ML tooling, agentic frameworks, or LLM-based applications is a strong plus
• Comfortable working in ambiguous environments, able to identify problems and propose solutions independently

Education

Bachelor's Degree in Computer Science, Mathematics, Applied Physics, Data Science, or a related field

Tools

Python

Pandas

Polars

Apache Spark

LangChain

LangGraph

RAG pipelines

PostgreSQL

Apache Iceberg

Job description

Qualifications

• Bachelor's Degree in Computer Science, Mathematics, Applied Physics, Data Science, or a related field

• 2 to 4 years in data engineering, platform engineering, MLOps, or operations-focused technical role.

• Hands-on experience building automation solutions or data pipelines in a production environment.

• Exposure to AI/ML tooling, agentic frameworks, or LLM-based applications is a strong plus.

• Comfortable working in ambiguous environments, able to identify problems and propose solutions independently.

Plus Points

• Proficient in Python, Pandas, Polars, and Apache Spark.

• Hands-on experience with LangChain, LangGraph, RAG pipelines, and prompt engineering.

• Familiar with PostgreSQL, Apache Iceberg

• Understand end-to-end AI architecture - RAG, agentic systems, multi-model workflows, APIs, and production deployment.

• Knowledgeable in ethical AI, bias mitigation, transparency, AI governance, and enterprise regulatory considerations.

• Strong grasp of data modeling, feature stores, dimensional modeling, and dataset structure for ML pipelines.