Autonomous Knowledge Engine for Security Operations
AI Engineer
Location
United States
Posted
8 days ago
Salary
0
Seniority
Senior
Job Description
AI Engineer
Crogl, Inc.
• 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.
Job 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.
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