AI Engineer: Build Scalable LLM Apps & Pipelines

Coderspace; Turkey; On-site; TRY 550,000 - 900,000; Full time

Benefits offered by this job

Meal allowance

Private health insurance

Commuting support

SOS leave (10 days)

Birthday leave

Language learning support

Personal development budget

Well-being platform

Relocation allowance

Top-tier work equipment

Cultural events tickets

Job summary

Paribu is seeking an AI Engineer to design, build, and operate production-grade LLM applications and AI-powered tools. You will develop scalable backend services, integrate with developer tools, and establish observability, governance, and cost controls across AI workflows.

You will collaborate with engineering and business teams to identify high-impact AI opportunities and drive end-to-end ownership from architecture to production.

Qualifications

• Hands-on experience building production-grade LLM applications and embeddings.
• Strong backend engineering with Python and/or TypeScript/Go, API design.
• Experience evaluating and monitoring LLM systems with metrics and tracing.
• Security, data governance, and auditability in AI systems.
• Experience integrating AI with GitHub, Slack, CI/CD and MCP-style integrations.

Responsibilities

• Design, build, and operate production-grade LLM applications and RAG pipelines.
• Develop scalable backend services and APIs powering AI products.
• Implement evaluation, observability, and cost optimization for models.
• Ensure secure, permission-aware AI systems with data governance.
• Collaborate with engineers and stakeholders to identify high-impact AI use cases.

Skills

LLM applications

RAG pipelines

agent/workflows

Python

TypeScript/Go

API design

Cloud & Kubernetes

Security & governance

GitHub & DevTools

Tools

GitHub

Slack

CI/CD pipelines

MCP-based tools

Job description

Paribu is seeking an AI Engineer to design, build, and operate production-grade LLM applications and AI-powered tools. You will develop scalable backend services, integrate with developer tools, and establish observability, governance, and cost controls across AI workflows.

You will collaborate with engineering and business teams to identify high-impact AI opportunities and drive end-to-end ownership from architecture to production.