About Dusker AI

Dusker AI specializes in benchmarking and evaluating AI agents to help organizations understand real-world performance. Using expert-driven frameworks, we evaluate AI systems across reasoning, reliability, adaptability, and safety to ensure they perform consistently in production environments. Our platform goes beyond traditional benchmarks to identify strengths, uncover critical gaps, and help build AI systems that are truly deployment-ready.

Role Overview

We are looking for a talented AI Agent Engineer to join our remote team. In this role, you will design, build, and optimize AI agents and the infrastructure used to evaluate their real-world performance. You'll work on agent frameworks, orchestration pipelines, benchmarking systems, and evaluation tools while collaborating with researchers and engineers to improve the reliability and effectiveness of modern AI systems.

What You'll Do

• Design and develop AI agents using modern agentic frameworks.
• Build and integrate agent orchestration pipelines and evaluation workflows.
• Develop benchmarking scenarios and automated test harnesses.
• Analyze agent performance across reasoning, reliability, safety, and robustness.
• Integrate LLMs, vector databases, APIs, and external tools into AI agents.
• Collaborate with research, product, and engineering teams to improve agent behavior.
• Maintain production-quality code and documentation.
• Contribute to internal tooling that streamlines AI evaluation and benchmarking.

Required Qualifications

• Strong programming skills in Python, TypeScript/JavaScript, or similar languages.
• Experience with LLMs, LangChain, LangGraph, PyTorch, TensorFlow, or other AI frameworks.
• Hands-on experience building AI agents or agentic workflows.
• Knowledge of AI evaluation, benchmarking methodologies, and performance metrics.
• Experience with APIs, distributed systems, cloud platforms (AWS, GCP, or Azure), and observability tools.
• Strong analytical, problem-solving, and communication skills.
• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.

Preferred Qualifications

• Experience with conversational AI or autonomous AI agents.
• Knowledge of AI safety, reliability, and model evaluation.
• Experience with vector databases, RAG pipelines, and prompt engineering.
• Familiarity with CI/CD, Docker, Kubernetes, or MLOps workflows.