AI Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop features, workflows, and agentic systems powered by LLMs that address genuine customer challenges.

• Design and execute evaluation frameworks to assess agent quality, reliability, and business impact.

• Create automated benchmarks, regression tests, and datasets for the evaluation of AI behavior.

• Analyze agent failures and formulate systematic strategies to enhance performance.

• Experiment with prompting techniques, tool usage, retrieval, memory, planning, and reasoning strategies.

• Construct infrastructure that facilitates rapid experimentation, evaluation, deployment, and monitoring.

• Collaborate closely with customers and internal teams to comprehend workflows and pinpoint opportunities for AI automation.

• Contribute to engineering best practices regarding testing, observability, and production reliability.

• Remain up-to-date with developments in LLMs, agents, evaluation methodologies, and AI engineering.

⛳️ Requirements

• Proficient programming skills, ideally in Python.

• Strong foundation in software engineering, including testing, debugging, and system design.

• Experience in developing applications, projects, or products utilizing LLMs and contemporary AI tools.

• Capability to design experiments, analyze results, and make data-informed decisions.

• Excellent communication skills with a willingness to work collaboratively across various disciplines.

• A sense of curiosity, ownership, and a keen desire to learn swiftly.

• Experience in creating AI agents, copilots, or workflow automation systems.

• Background in 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.

• Knowledge of 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.

• Contributions to open-source projects, research initiatives, or personal AI products.

🏝️ Benefits

• Engage with some of the most complex challenges in applied AI.

• Play a key role in defining the evaluation and deployment of agentic systems in a production environment.

• Join a small, highly collaborative team where you can make a significant impact and enjoy substantial ownership.

• Accelerate your learning while working alongside seasoned engineers, researchers, and security professionals.

• Help shape the future of AI-driven security operations.