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Location
Remote (Philippines)
Seniority
Middle · 3+ years exp

Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on Jul 20, 2026. KDCI scores B on the Alion truth index.

Overview
Company
Impact
Profile match
KDCI, or Key Discovery Consulting, is an offshore staffing and outsourcing company that builds dedicated full-time remote teams in the Philippines for overseas clients, with its delivery center in Pasig and a US office in Carson, California. Founded in 2011 by executives with long outsourcing experience, it supplies staff for accounting, customer support, legal operations, creative production, engineering and AI work. Its openings, all based in Pasig, include accounting and accounts payable specialists, SaaS and customer support specialists, power systems engineers, CAD drafters, graphic and AI image designers, social media specialists and AI and automation engineers.

Role Summary

KDCI Outsourcing is looking for an LLM Engineer to design, fine-tune, and deploy large language model solutions that solve real business problems. You'll work across the model lifecycle - from prompt and architecture design to evaluation and production monitoring - collaborating with product and engineering teams to ship reliable AI features.

Key Responsibilities

  • Design, fine-tune, and optimize large language models for specific use cases

  • Build and maintain evaluation harnesses to measure model quality and safety

  • Implement RAG (retrieval-augmented generation) pipelines and prompt strategies

  • Monitor model performance in production and iterate on improvements

  • Collaborate with product and engineering teams to integrate LLM features

  • Stay current with emerging LLM research, architectures, and tooling

Requirements

Requirements

  • 3+ years of hands-on experience with large language models and NLP

  • Strong understanding of transformer architectures (GPT, BERT, LLaMA, etc.)

  • Proficiency in Python and ML frameworks such as PyTorch or TensorFlow

  • Experience with fine-tuning, prompt engineering, and hyperparameter optimization

  • Track record of deploying ML/LLM systems in production environments

Nice-to-Haves

  • Experience with vector databases and RAG pipelines

  • Familiarity with model quantization and inference optimization

  • Background in AI safety or content moderation systems

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