Drimva

Veeva Systems

Technical Curriculum Developer - AI Agents - Remote

$100K–$175K

California - Pleasanton · Remote · Full-time · Posted Aug 7, 2026

Experience
3+ years building technical training, curriculum, or enablement content.
Education
Bachelor’s degree in Computer Science, Engineering, Instructional Design, or equivalent practical experience.

About the job

Develop technical training and hands-on labs for Veeva’s platform and Agentic AI capabilities, while building AI agent demos and maintaining advanced Java- and REST API-focused courses.

What you'll do

  • Design technical AI-agent curriculum, labs, demos, and reference implementations.
  • Own advanced technical courses and maintain lab environments, sample code, and exercises.
  • Collaborate with Product, Engineering, Services, and Support to develop courseware and address learner needs.

What they ask for

  • Hands-on experience building, configuring, and deploying AI agents; practical understanding of agent concepts including tool calling, RAG, context management, orchestration, prompting, and evaluation.
  • Ability to understand Java code architecture and classes, foundational REST API knowledge, and experience with Git, Postman, or similar tools.
  • 3+ years building technical training, curriculum, or enablement content for a technical audience; experience designing hands-on labs and courses.
  • Bachelor’s degree in Computer Science, Engineering, Instructional Design, or equivalent practical experience.

Nice to have

  • Experience with MCP or comparable tool-integration standards.
  • Familiarity with LMS platforms and AI/authoring tools; experience with Veeva Vault or complex enterprise SaaS platforms.

Pay

USD 100,000 - $175,000 base salary

Tools

LangChain, LangGraph, Anthropic's Claude Agent SDK/Claude Code, Model Context Protocol (MCP), Java, REST APIs, Git, Postman

AI focus

Build and teach implementation of AI agents, including demos and labs covering tool calling, RAG, context and memory management, multi-agent orchestration, prompt engineering, and evaluation.

Model-written summary · the original posting is authoritative

First seen Oct 29, 2026 · Last verified Nov 4, 2026 (UTC)