AI Engineer

Crogl, Inc.

AI Engineer developing LLM-powered features and workflows for security automation at Crogl. Collaborating with teams to build and evaluate AI systems for security investigations.

Posted 6/30/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building LLM-powered features and AI systems, with strong programming skills in Python and experience in designing evaluation frameworks and automated testing for AI behavior. Capable of collaborating across disciplines to drive AI automation and improve system performance.

Highest-signal resume keywords

Python ProgrammingLLM Application DevelopmentAI Evaluation Framework DesignAutomated Testing and BenchmarkingCollaboration and Communication

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Hard Skills

Software Engineering FundamentalsExperiment Design and Data AnalysisAI Agent DevelopmentRetrieval SystemsVector DatabasesRAG ArchitecturesObservability and MonitoringDebuggingSystem DesignTesting Frameworks

Soft Skills

Strong CommunicationCuriosityOwnershipWillingness to CollaborateDesire to Learn Quickly

Tools & Technologies

OpenAIAnthropicGeminiLangGraphOpenAI Agents SDKMCPAI Automation ToolsObservability ToolsProduction Monitoring ToolsCybersecurity Tools

Industry Keywords

AI EngineeringLLM EcosystemsAgentic SystemsWorkflow AutomationCybersecurity

Tech Stack

Tools & technologies

Cyber SecurityPython

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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.