AI/LLM Platforms Engineer

ERNI - Swiss Software Engineering

Mandaluyong

Hybrid

PHP 900,000 - 1,400,000

Full time

14 days+

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Job summary

ERNI - Swiss Software Engineering in the Philippines seeks an AI/LLM Support Engineer to bridge operations, development, and business stakeholders. You will investigate incidents, troubleshoot integrations, and support AI-enabled applications across Databricks, Spark, and cloud platforms, collaborating with global teams to ensure reliable services.

Join a team that values structured analysis, continuous learning, and service improvements, with hybrid work and opportunities for growth within a

Qualifications

Experience in Application Support, Production Support, Technical Support, or similar roles.
Strong analytical and problem-solving skills.
Knowledge of APIs, system integrations, and web services.
Understanding of networking fundamentals.
Experience with Python scripting.
Ability to analyze technical logs, payloads, and application workflows.
Strong written and spoken English communication skills.
Ability to create clear and structured technical documentation.
Detail-oriented mindset with a passion for troubleshooting and continuous learning.
Ability to perform prompt engineering concepts and AI workflows.
Experience with AI, Machine Learning, or Large Language Model applications.
Experience working with ServiceNow or other ITSM platforms.
Understanding of Incident Management and IT Operations processes.
Experience working in global, enterprise-scale environments.
Experience with Microservices Architecture.
Experience working in Agile or Scrum environments.
Exposure to integration, user acceptance, security, and performance testing.
Master's Degree in a related discipline is an advantage.

Responsibilities

Investigate incidents, troubleshoot integrations, and support AI-enabled applications.
Collaborate with global teams to diagnose issues and document solutions.
Provide operational support for Databricks-based enterprise data platforms.
Investigate and resolve incidents affecting data pipelines, workflows, clusters, integrations.
Troubleshoot Spark, PySpark, Spark SQL, and ETL/ELT workloads in production.
Monitor platform health and identify risks before they impact users.
Support incident management, root cause analysis, and problem management activities.
Create and maintain technical runbooks and knowledge base articles.
Contribute to automation initiatives and service improvement.