Mid AI/LLM Engineer (Remote)

Lewis Personnel Management; Manila; Remote; PHP 900,000 - 1,500,000; Full time

Job summary

Lewis Personnel Management is seeking an AI Engineer / LLM Engineer to turn AI concepts into production-grade applications using Snowflake and large language models. This hands-on role focuses on building, deploying, monitoring, and maintaining AI systems in production.

You will collaborate with data scientists and engineers to implement LLM solutions, optimize data workflows, and establish CI/CD pipelines for reliable, scalable AI services in Manila.

Qualifications

• 3–5 years of experience in AI, ML, data engineering, or software engineering.
• Strong proficiency in Python and SQL.
• Hands-on experience with Snowflake, including data preparation and tuning.
• Proven experience deploying and maintaining production LLM applications, esp. RAG systems and AI agents.
• Experience with prompt management, LLM evaluation, testing, CI/CD, monitoring, and troubleshooting live systems.
• Strong problem-solving skills and translating requirements into production-ready solutions.

Responsibilities

• Build, deploy, and maintain production-ready AI applications on Snowflake, including LLM-powered applications, RAG, and AI agents.
• Translate AI designs into scalable, reliable production services.
• Develop and optimize data preparation workflows, SQL queries, and integrations within Snowflake.
• Implement LLM solutions, including prompt management, evaluation, and performance optimization.
• Establish and maintain CI/CD pipelines, automated testing, monitoring, and incident troubleshooting for live AI systems.
• Collaborate with data scientists and engineering teams to ensure AI solutions meet business requirements and production standards.
• Monitor application performance, troubleshoot issues, and continuously improve the reliability and efficiency of deployed AI systems.

Skills

Python

SQL

Snowflake

LLM deployment

RAG systems

CI/CD

Tools

Snowflake Cortex

LLM evaluation tools

Observability tools

Prompt management tools

Job description

We’re looking for an AI Engineer / LLM Engineer who can turn AI concepts into reliable, production-ready applications using Snowflake and large language models (LLMs).

This is a hands‑on engineering role focused on building, deploying, monitoring, and maintaining production AI systems—not AI research.

Responsibilities

• Build, deploy, and maintain production-ready AI applications on Snowflake, including LLM-powered applications, Retrieval-Augmented Generation (RAG), and AI agents.

• Translate AI designs and technical direction into scalable, reliable, and monitored production services.

• Develop and optimize data preparation workflows, SQL queries, and integrations within Snowflake.

• Implement LLM solutions, including prompt management, evaluation, and performance optimization.

• Establish and maintain CI/CD pipelines, automated testing, monitoring, and incident troubleshooting for live AI systems.

• Collaborate with data scientists and engineering teams to ensure AI solutions meet business requirements and production standards.

• Monitor application performance, troubleshoot issues, and continuously improve the reliability and efficiency of deployed AI systems.

Qualifications

• 3–5 years of experience in AI, Machine Learning, Data Engineering, or Software Engineering.

• Strong proficiency in Python and SQL.

• Hands‑on experience with Snowflake, including data preparation, performance tuning, and integrations.

• Proven experience deploying and maintaining production LLM applications, particularly RAG systems and AI agents.

• Experience with prompt management, LLM evaluation, testing, CI/CD, monitoring, and troubleshooting live systems.

• Strong problem‑solving skills and the ability to translate technical requirements into production‑ready solutions.

Nice to Have

• Experience with Snowflake Cortex, including Cortex Agents, Search, or Analyst, and/or Snowpark.

• Familiarity with LLM evaluation and observability tools.

• Experience with traditional ML pipelines, including model deployment, drift monitoring, and retraining.

• Exposure to the Microsoft AI ecosystem, such as Azure AI, Power Platform, or Microsoft Copilot.

Requirements

Please refer to job description.

Python Machine Learning Deep Learning Data Analysis Neural Networks Statistical Analysis Model Deployment Data Engineering Algorithm Design

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