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Job Overview:
Master Works is looking for a highly skilled LLM Engineer to join our AI Core Delivery team within the AI & Analytics CoE. In this role, you will develop, deploy, and optimize advanced language model capabilities, including Retrieval-Augmented Generation (RAG) pipelines and agentic AI systems. You will play a key role in scaling AI Core as the central enterprise AI platform by ensuring production-ready performance, robust observability, and seamless integration of LLMs with internal and external systems.
Key Responsibilities
- Model Development & Optimization
- Build and optimize RAG pipelines for efficient document processing, indexing, and retrieval.
- Implement agentic AI logic for tool integration, task automation, and external data access.
- Enhance query understanding, response ranking, and AI-generated output quality.
- Develop evaluation benchmarks to measure LLM performance, accuracy, and relevance.
- LLMOps & Deployment
- Collaborate with API developers and backend engineers to deliver secure, observable LLM endpoints.
- Deploy and manage LLMs in cloud-native or hybrid environments with support for scalability and multi-cloud readiness.
- Implement CI/CD workflows for model updates, rollback mechanisms, and performance tuning.
- Backend & Data Integration
- Integrate LLM capabilities with enterprise data sources and knowledge bases.
- Support multi-source retrieval and embedding strategies to improve AI responses.
- Design pipelines that ensure low latency, high throughput, and fault tolerance.
- Security & Compliance
- Apply enterprise-grade authentication, access management, and encryption standards.
- Ensure compliance with internal governance policies, data privacy, and audit requirements.
- Continuous Improvement
- Monitor system performance, debug issues, and fine-tune models based on real-world feedback.
- Stay updated on advancements in LLM architectures, open-source tools, and evaluation frameworks.