GenAIEngineer-AgenticERPPlatform

## Accountabilities Design and build AI agents using Python and frameworks such as Pydantic AI to automate ERP workflows and enterprise business processes. Implement MCP-based tool integrations enabling agents to interact with ERP systems, databases, and external enterprise services. Develop multi-step agent workflows with decision branching, error handling, and human-in-the-loop escalation logic. Engineer system prompts, templates, and guardrails that define agent behavior, constraints, and enterprise-safe responses. Build and optimize context engineering strategies, including memory systems, retrieval-augmented context, and token-efficient summarization. Integrate and orchestrate LLMs using gateways such as LiteLLM, ensuring routing, fallback handling, and performance optimization. Develop evaluation frameworks to measure agent accuracy, reliability, and task success rates across enterprise use cases. Implement safety, security, and compliance guardrails, including prompt injection detection, audit logging, and output validation. Requirements: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field. 5–8 years of software engineering experience, including at least 2+ years in GenAI, LLM, or AI-driven application development. Strong Python expertise with production-level experience in async programming and scalable system design. Hands-on experience building LLM-powered applications, agents, or chatbots in production environments. Deep understanding of prompt engineering, including system prompts, few-shot learning, structured outputs, and evaluation methods. Experience with LLM APIs (OpenAI, Anthropic, or similar), including tool calling, streaming, and structured responses. Familiarity with agent frameworks such as Pydantic AI, LangChain, or LlamaIndex. Knowledge of context window optimization, token management, and LLM limitations. Experience with API integrations, REST/JSON systems, and enterprise software architectures. St