Key Responsibilities for AI Developer:
Design and implement scalable architectures for AI agents using LangGraph and the A2A protocol
Build robust evaluation pipelines to benchmark agent behavior, quality, and performance (e.g., using AI evals, custom metrics)
Fine-tune and optimize system prompts and agent configurations for specific tasks and workflows
Ensure scalability, fault tolerance, and performance tuning of agent systems in production environments
Manage deployment workflows using tools like Docker, Kubernetes, and CI/CD pipelines
Implement logging, monitoring, and feedback loops to continuously improve agent performance and reliability
Requirements:
Hands-on experience deploying and scaling AI agents in production environments
Strong familiarity with LangGraph and Agent-to-Agent (A2A) communication protocols
Experience with AI evaluation techniques, prompt iteration workflows, and outcome benchmarking
Proven ability to fine-tune system prompts and agent behaviors for robustness and alignment
Proficiency in Python and experience working with modern ML/LLM frameworks (LangChain, OpenAI, etc.)
Experience with containerization (Docker), CI/CD, and cloud-based deployment infrastructure
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