AI Agentic Developer

Job Description

General Experience

45 years of overall software / integration engineering experience, including approximately 2 years of hands-on AI / Agentic AI experience.
Proven delivery of production integrations in an enterprise environment.

MuleSoft Integration Expertise

Hands-on experience on the MuleSoft Anypoint Platform API-led design, DataWeave, connectors, error handling, and CloudHub deployment. MuleSoft Developer certification preferred.
Strong REST/SOAP, JSON/XML, OAuth, and API-security fundamentals; comfortable with email, file, and database connectivity patterns.
Exposure to SAP order entry, pricing, drop-ship, and customer master data is a strong plus; ability to translate business rules into deterministic automation logic.

AI / Agentic AI Skill Set

Exposure to AI/ML concepts LLM-based agents, prompt engineering, or agentic workflows.
Understanding of AI agent architectures multi-agent orchestration, tool-use patterns, and autonomous task execution.
Knowledge of agentic frameworks such as LangChain, LangGraph, or similar.
Experience building or integrating RAG (Retrieval-Augmented Generation) pipelines with vector databases.
Familiarity with caching strategies and memory / context management for AI agents (conversation history, session persistence, vector stores).
Experience with agent deployment and serving (Databricks preferred), MLflow, or similar platforms.
Familiarity with MCP (Model Context Protocol) or AI-assisted automation.
Python scripting for automation or tooling.

Engineering Practices Ways of Working

CI/CD, version control, automated testing, and monitoring; writes clear technical documentation and supports UAT and go-live.
Self-directed delivery with strong communication skills; comfortable operating across overlapping time zones with global stakeholders.

Nice to Have

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