AI Engineer

Role Overview

This role gets AI into production and keeps it running. You own the MLOps backbone and build the agentic systems we deliver for clients: agents, GraphRAG, enterprise copilots, and workflow automation. The focus is on making LLM systems dependable, reliable, affordable, and guarded within real-world client workflows.

Responsibilities

• Design and ship agentic systems including agents, RAG, GraphRAG, and copilots.
• Own model-specific production logic: serving, evaluation, guardrails, drift monitoring, and retraining loops.
• Build MLOps frameworks and reusable AI infrastructure.
• Expose models and agents behind clean endpoints for application consumption.
• Integrate AI into real operational workflows.

Requirements

• Proven ability to turn models and graph foundations into dependable production AI.
• Expertise in model behavior, serving logic, and evaluation.
• Strong software engineering practices: tested, reviewed, and versioned code.
• An MLOps mindset focused on monitoring, retraining, and drift management.
• Systems thinking and a commitment to quality and security.

Skills

• Python
• FastAPI
• PyTorch
• Neo4j
• MLOps

Benefits

• Flexible schedule
• Work from home