Technical Curriculum Developer

About the role

This role designs and delivers advanced technical training and AI agent curriculum for customers, partners, and Veevans. The position targets individuals with an engineering background who can mentor AI agent development and build rigorous, code‑focused courses. You will own the full training lifecycle for agentic AI capabilities on the Veeva platform.

Software engineers turn product ideas into working code. Engineers work in small teams, review each other's work, and ship in small batches. Most teams follow agile practices such as sprints and daily standups. Engineers also write tests, fix bugs, and improve performance. The field values clear communication as much as technical skill. Engineers spend part of every week on planning, code review, and debugging, not just writing new code. The ability to explain a technical decision in plain words separates strong engineers from the rest.

Key facts

Requirements

Hold a Bachelor's degree in Computer Science, Engineering, Instructional Design, or equivalent practical experience.

Have hands‑on experience building, configuring, and deploying AI agents using frameworks or SDKs such as LangChain, LangGraph, Anthropic's Claude Agent SDK, or similar.

Demonstrate practical understanding of core agent concepts: tool and function calling, retrieval‑augmented generation, context and memory management, multi‑agent orchestration, prompt engineering, and evaluation.

Have experience with the Model Context Protocol (MCP) or comparable tool‑integration standards as a strong plus.

Have first‑hand experience troubleshooting real agent builder problems - flaky tool calls, context overflow, hallucinated actions, and permission or scoping issues - so you can teach learners to anticipate and solve them.

Ability to read and understand Java code architecture and classes for minor development or debugging, alongside a strong foundational knowledge of REST APIs.

Experience with Git, Postman, or similar API tooling.

Possess 3+ years of experience building technical training, curriculum, or enablement content for a technical audience of developers, implementation consultants, technical admins, or power users.

Experience designing hands‑on labs, sandbox exercises, and high‑quality instructor‑led courses and/or eLearning.

Familiarity with LMS platforms and AI/authoring tools such as Articulate, Camtasia, Arcade, Vyond, Gemini, or Claude is a plus.

Have the ability to quickly ramp up on complex enterprise SaaS platforms such as Veeva Vault and how they are configured and implemented by customers.

Be self‑directed and comfortable with ambiguity while defining curriculum for capabilities that are still being built.

Demonstrate strong writing and technical communication skills to explain complex technical concepts clearly to varied audiences, both technical and semi‑technical.

Show strong presentation and facilitation skills for leading live demos and workshops.

Practical notes

Veeva is an equal opportunity employer; all qualified applicants receive consideration without regard to protected characteristics.

Typical interview steps

Hiring for engineering roles usually starts with a recruiter screen, followed by one or two technical rounds. Candidates often solve a coding problem, discuss past projects, and answer system design questions. Some loops include a take-home task. Final rounds typically cover team fit and give candidates a chance to ask questions. Interviewers look for how you break down an unfamiliar problem, not just whether you reach the answer. Practicing a few problems aloud and reviewing your own past projects are the best preparation.

Good to know

The role focuses on developing curriculum and enablingment for technical and agentic AI topics.

Success requires deep technical fluency in Java, REST APIs, and modern AI agent frameworks.

The position involves close collaboration with product, engineering, and customer success teams.

Instructional design rigor must balance accessibility with technical precision.

The role may involve frequent context switching across multiple products and customer scenarios.