Senior LLM Architect – On-Prem AI & RAG Systems

Oredata; Fatih; On-site; TRY 700,000 - 1,400,000; Full time

Benefits offered by this job

Private Health Insurance

Birthday Leave

Professional Certificates sponsorship

Online Training Platforms access

Job summary

Oredata is seeking a Data Scientist (LLM) to lead enterprise AI projects in aviation, focusing on LLMs, RAG, and on-premise infrastructure. You will design scalable, production-ready AI solutions, optimize performance, and collaborate with cross-functional teams to deliver high-impact results.

You will drive architecture decisions for AI platforms, champion efficient GPU utilization, and help build agentic AI capabilities across internal tools and applications.

Qualifications

• Minimum 7 years in AI, ML, DS, or related roles.
• Hands-on with LLMs and Generative AI in production.
• Experience deploying and serving LLMs, on-prem or private cloud.
• Designing scalable AI systems for high-traffic environments.
• Strong Python and software engineering practices.

Responsibilities

• Design, develop, test, and productionize LLM-based and RAG solutions for enterprise use cases.
• Hands-on role in internal chatbot, conversational AI, knowledge assistant, and agentic AI products.
• Own architecture of enterprise LLM solutions, including model selection and deployment.
• Deploy, operate, and optimize open-weight and commercial LLMs, with focus on on-premise infrastructure.
• Evaluate models considering quality, latency, cost, security and governance.
• Optimize inference and infrastructure using quantization, batching, caching, and routing.

Skills

LLMs & Generative AI

Production AI systems

GPU inference

Python programming

Kubernetes/OpenShift

RAG-based apps

AI governance

Tools

Kubernetes

OpenShift

Hugging Face

NVIDIA inference

Triton

vLLM

Job description

Oredata is seeking a Data Scientist (LLM) to lead enterprise AI projects in aviation, focusing on LLMs, RAG, and on-premise infrastructure. You will design scalable, production-ready AI solutions, optimize performance, and collaborate with cross-functional teams to deliver high-impact results.

You will drive architecture decisions for AI platforms, champion efficient GPU utilization, and help build agentic AI capabilities across internal tools and applications.