AI Engineer - Legal Tech & Production Systems

Apilex; Şişli; On-site; TRY 450,000 - 600,000; Full time

Job summary

Apilex is an AI-native legal operating system that manages lawyers' workflows end to end. We seek an AI Engineer to design, build, and operate AI systems powering legal research, drafting, and case preparation across jurisdictions.

You will own technically challenging projects and collaborate with researchers, engineers, and domain experts to deliver reliable production systems. Role emphasizes graph-based knowledge representations, multi-agent coordination, and production-grade tooling.

Qualifications

• 5+ years of engineering experience building and operating AI or ML systems in production.
• Strong Python. You have designed systems others build on, and you care about boundaries, types and tests.
• Agentic systems, hands-on. Tool use, state across multi-step tasks, and recovery when a model returns something the schema did not expect.

Responsibilities

• Design, build, and improve AI systems for complex legal reasoning and long-horizon task execution.
• Develop agentic systems that can plan, use tools, manage state, recover from errors, and complete end-to-end workflows.
• Build graph-based multi-agent orchestration systems representing workflows, dependencies, and state transitions.
• Design and implement graph engineering across GraphRAG, personalized knowledge bases, and multi-agent orchestration.
• Build GraphRAG systems connecting structured and unstructured legal knowledge to improve retrieval and reasoning.

Skills

Python programming

Production AI systems

System design

Tools

GraphRAG

Graph databases

Neo4j

Job description

Apilex is an AI-native legal operating system that manages lawyers' workflows end to end. We seek an AI Engineer to design, build, and operate AI systems powering legal research, drafting, and case preparation across jurisdictions.

You will own technically challenging projects and collaborate with researchers, engineers, and domain experts to deliver reliable production systems. Role emphasizes graph-based knowledge representations, multi-agent coordination, and production-grade tooling.