Intermediate AI Engineer – Python, RAG, Agentic AI, Vertex AI, WatsonX

About the role

UPS is looking for an AI Engineer with 5+ years of overall experience in software development, data science or machine learning to design, develop and deploy AI systems based on large language models (LLMs), chatbots, retrieval-augmented generation (RAG) and agentic AI. The role involves hands-on work with LLMs, embeddings, RAG pipelines and multi-agent systems using LangChain, LangGraph and LlamaIndex, and experience with Vertex AI on GCP and IBM WatsonX.

Key responsibilities

• Design, build and deploy agentic AI systems and multi-agent systems that reason, plan and collaborate autonomously.
• Implement and optimise RAG systems so agents can use external knowledge sources.
• Fine-tune and prompt-engineer LLMs and work with LLM/SLM APIs and embeddings.
• Lead enterprise-grade AI platforms and implement the Model Context Protocol (MCP).
• Set up MLOps, monitoring and observability practices.
• Rapidly prototype AI agents and take part in the research cycle, from data exploration to presenting findings.
• Collaborate with engineers, researchers and data scientists and contribute to code documentation.

Required profile

• Bachelor's degree in computer science, engineering or a related quantitative field; master's or PhD is a strong plus.
• 5+ years of overall experience in software development, data science or machine learning.
• 1+ year of hands-on AI application development with LLMs, retrieval-based methods, fine-tuning or agent-based architectures.
• 1+ year of experience with LangChain, LlamaIndex, OpenAI or similar tools.

Required skills

• Python and basic SQL.
• Expertise with LLM/SLM APIs, embeddings and RAG systems.
• Deployment experience on Google Cloud Platform (Vertex AI) and IBM WatsonX.
• Preferred: MCP, LangGraph, AutoGen, MLOps (CI/CD for ML, observability), responsible AI principles, open-source contributions.