AI Engineer

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Crogl, Inc.

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2023

🔒 Cybersecurity

☁️ SaaS

Cybersecurity • AI • SaaS

Crogl, Inc. is the only autonomous knowledge engine for security operations that investigates alerts and executes threat hunts by learning organizational processes. It continuously analyzes and documents every alert across various environments, empowering security analysts to make informed decisions without needing deep technical expertise. With features such as seamless SIEM migration, audit readiness, and automated investigations, Crogl helps security teams enhance their efficiency and effectiveness in handling cyber threats.

📋 Description

• Build LLM-powered features, workflows, and agentic systems that solve real customer problems. • Design and implement evaluation frameworks to measure agent quality, reliability, and business impact. • Create automated benchmarks, regression tests, and datasets for evaluating AI behavior. • Investigate agent failures and develop systematic approaches to improve performance. • Experiment with prompting, tool use, retrieval, memory, planning, and reasoning strategies. • Build infrastructure that supports rapid experimentation, evaluation, deployment, and monitoring. • Work closely with customers and internal teams to understand workflows and identify opportunities for AI automation. • Contribute to engineering best practices for testing, observability, and production reliability. • Stay current with advances in LLMs, agents, evaluation methodologies, and AI engineering.

🎯 Requirements

• Strong programming skills, preferably in Python. • Solid software engineering fundamentals, including testing, debugging, and system design. • Experience building applications, projects, or products using LLMs and modern AI tools. • Ability to design experiments, interpret results, and make data-driven decisions. • Strong communication skills and willingness to collaborate across disciplines. • Curiosity, ownership, and a desire to learn quickly. • Experience building AI agents, copilots, or workflow automation systems. • Experience designing evaluations, benchmarks, or testing frameworks for AI systems. • Familiarity with OpenAI, Anthropic, Gemini, or open-source LLM ecosystems. • Experience with retrieval systems, vector databases, and RAG architectures. • Familiarity with LangGraph, OpenAI Agents SDK, MCP, or similar agent frameworks. • Experience with observability, tracing, and production monitoring for AI systems. • Exposure to cybersecurity, security operations, or developer tooling. • Open-source contributions, research projects, or personal AI products.

🏖️ Benefits

• Work on some of the most challenging problems in applied AI. • Help define how agentic systems are evaluated and deployed in production. • Join a small, highly collaborative team with significant ownership and impact. • Learn quickly while working alongside experienced engineers, researchers, and security experts. • Shape the future of AI-powered security operations.