Jobs via Dice ยท 1 day ago
Agentic AI Developer
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Lorven Technologies, Inc., is seeking an Agentic AI Developer to design and implement scalable architectures for AI agents and manage deployment workflows. The role requires proficiency in AI technologies and experience in production environments.
Computer Software
Responsibilities
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
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
Qualification
Required
Bachelor's or Master's degree in Computer Science, Information Systems, Finance, Data Engineering or a related field
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
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
Company
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Funding
Current Stage
Early StageCompany data provided by crunchbase