AI Engineer
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Key skills for this role
Role Overview
Crogl builds AI-powered systems that help security teams investigate, understand, and respond to threats.
The AI Engineer will design, evaluate, and improve production agentic systems while working with customers, engineers, and product teams.
This is a mid-level engineering role focused on practical AI products, LLMs, and agent systems.
Key Skills for This Role
Full Job Posting
Role overview
Crogl builds AI-powered systems that help security teams investigate, understand, and respond to threats.
The AI Engineer will design, evaluate, and improve production agentic systems while working with customers, engineers, and product teams.
This is a mid-level engineering role focused on practical AI products, LLMs, and agent systems.
What you will do
- Build LLM-powered features, workflows, and agentic systems for real customer problems.
- Design evaluation frameworks that measure agent quality, reliability, and business impact.
- Create benchmarks, datasets, automated evaluations, and regression testing pipelines.
- Investigate agent failures and improve prompting, tools, retrieval, memory, planning, and reasoning.
- Build infrastructure for AI experimentation, evaluation, deployment, observability, and monitoring.
- Work with customers and internal teams to understand workflows and identify automation opportunities.
- Contribute to testing, observability, and production reliability practices.
AI evaluation focus
- Evaluate whether agents produce accurate investigations and improve customer outcomes.
- Detect regressions before customers experience them and identify important failure modes.
- Measure reliability, trustworthiness, business impact, and production agent performance.
What you will bring
- Strong programming skills, preferably in Python.
- Software engineering fundamentals including testing, debugging, and system design.
- Experience building applications, projects, or products with LLMs and modern AI tools.
- Ability to design experiments, interpret results, and make data-driven decisions.
- Strong communication and willingness to collaborate across disciplines.
- Curiosity, ownership, and a desire to learn quickly.
Standout qualifications
- Experience building AI agents, copilots, or workflow automation systems.
- Experience designing AI evaluations, benchmarks, or testing frameworks.
- Familiarity with major or open-source LLM ecosystems, retrieval, vector databases, and RAG.
- Familiarity with LangGraph, OpenAI Agents SDK, MCP, or similar agent frameworks.
- Experience with AI observability, tracing, and production monitoring.
- Exposure to cybersecurity, security operations, or developer tooling.
Example projects
Build evaluation suites for AI-driven security investigations.
Create automated regression tests for model and prompt changes.
Develop datasets and benchmarks reflecting real customer workflows.
Build systems that identify and categorize agent failures.
Design feedback loops that improve production agent performance.
Success in the first six months
Ship improvements to production AI systems used by customers.
Help establish rigorous evaluation practices across the company.
Contribute ideas that improve agent performance and reliability.
Develop a strong understanding of customer workflows and security investigations.
Become a trusted contributor across engineering, product, and AI initiatives.
About Crogl
Crogl offers work on applied AI, agent evaluation, production deployment, and AI-powered security operations.
The team is small and collaborative, with significant ownership and impact alongside engineers, researchers, and security experts.
About crogl
AI-powered knowledge engine for autonomous security operations.
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