Senior AI Engineer: LLMs, Agents & Scalable Systems

Snapp!; General Trias; On-site; PHP 900,000 - 2,100,000; Full time

Job summary

Snapp! is seeking an AI Engineer to build scalable AI solutions across agents, search, and foundation-model-based apps.

You will own projects end-to-end from research to deployment, collaborating with product and engineering teams to translate business needs into concrete technical plans. You will design and deploy LLM-powered applications, explore prompt engineering and RAG, and optimize performance, latency, and costs while ensuring robust data privacy and reliability.

Qualifications

• Bachelor's degree or higher in Computer Science, Computer Engineering, Artificial Intelligence, or related field.
• At least 3 years of experience in AI engineering, ML, or software engineering focused on AI-powered products.
• Hands-on experience building and deploying ML or foundation-model-based solutions.

Responsibilities

• Collaborate with product and engineering teams to translate business needs into technical plans.
• Design, build, and deploy LLM-powered applications and AI agents.
• Select and adapt foundation models using prompt engineering, RAG, and fine-tuning.
• Contribute to semantic search, ranking, and speech initiatives.
• Create evaluation datasets and experiments to measure model quality.
• Write production-quality code and participate in deployment and monitoring.
• Optimize model quality, latency, and resource use.
• Document decisions and share best practices.

Skills

Python

Software engineering

API integration

Testing

Linux

Docker

PyTorch

Problem solving

Education

Bachelor's degree or higher in CS/CE/AI

Tools

PyTorch

Docker

Linux

Job description

Snapp! is seeking an AI Engineer to build scalable AI solutions across agents, search, and foundation-model-based apps.

You will own projects end-to-end from research to deployment, collaborating with product and engineering teams to translate business needs into concrete technical plans. You will design and deploy LLM-powered applications, explore prompt engineering and RAG, and optimize performance, latency, and costs while ensuring robust data privacy and reliability.