Artificial Intelligence Engineer

Overview

Most AI roles right now are experimentation.

This isn’t one of them.

We are looking for someone who has

actually built and deployed AI systems into production

. Not demos. Not notebooks. Real systems with users, failure modes, and performance constraints.

You will lead the design and delivery of agentic AI systems that need to operate reliably in enterprise environments.

What You’ll Own

• Architecture and delivery of agent-based AI systems
• End-to-end LLM pipelines including orchestration, tool use, and retrieval
• Designing systems with memory, reasoning, and controlled execution
• Translating unclear business problems into working AI systems
• Setting technical direction across AI, backend, and infrastructure
• Mentoring engineers and raising the bar on production quality

Core Requirements

• 8\+ years building AI/ML or intelligent systems in production
• Proven experience deploying LLM or AI systems beyond prototype stage
• Strong experience with RAG, retrieval systems, and embeddings
• Hands-on with agent frameworks (LangGraph, LangChain, AutoGen, CrewAI, etc.)
• Strong Python experience building scalable systems
• Experience designing systems, not just contributing to them
• Cloud experience (AWS, GCP, or Azure)

Strong Signals

• Built multi-agent systems with orchestration and coordination
• Experience with memory systems, state handling, and retries
• Designed guardrails, evaluation frameworks, or observability for AI
• Worked on systems where reliability and failure handling mattered