AI Engineer

Description

What We're Looking For

We're looking for an AI Engineer to shape the intelligence layer of Linx, our AI-native identity security platform. You'll build the AI brain behind our assistant, Autopilot , and identity-specific agents that detect, investigate, and remediate identity risks for some of the world's largest enterprises. This is a hands-on role for someone who thrives on solving complex technical challenges, turning cutting-edge AI ideas into production, and shaping the technical direction of our platform.

You'll partner with backend, product, security research, and data teams to build AI systems that are scalable, reliable, and trusted by some of the world's largest enterprises.

What You'll Do

Own AI features end-to-end, from problem definition and architecture through production and continuous improvement. Develop production-grade LLM applications using retrieval, tool calling, orchestration, structured outputs, and evaluation. Build trustworthy AI with robust guardrails, validation, observability, and human-in-the-loop workflows.

Drive architectural decisions across data, models, scalability, latency, and cost. Collaborate across backend, product, security research, and data to solve complex identity security challenges. Continuously improve AI performance through experimentation, measurement, and iteration.

Requirements

Proven experience building production AI agents or backend systems that deliver real customer impact. Hands-on experience developing and deploying LLM-powered applications, including agentic workflows, tool calling, retrieval, orchestration, and evaluation. Strong software engineering skills in Python (or similar), with experience building scalable backend systems.

Strong system design skills with the ability to make thoughtful technical trade-offs across scalability, latency, reliability, and cost. A builder mindset with a passion for solving complex problems, taking ownership, and turning ambitious ideas into production. Advantage: Experience building Text-to-SQL, Text-to-Query, or NL-to-data systems over complex or graph-based data.

Experience building agentic systems in production, including tool routing, long-running workflows, and failure handling. Familiarity with RAG, evaluation frameworks, MCP, or graph-based data.