Interested in this AI Agent Developer role at Veeva Systems?
Apply Now →Skills & Technologies
About This Role
Veeva Systems is a mission\-driven organization and pioneer in industry cloud, helping life sciences companies bring therapies to patients faster. As one of the fastest\-growing SaaS companies in history, we surpassed $3B in revenue in our last fiscal year with extensive growth potential ahead.
At the heart of Veeva are our values: Do the Right Thing, Customer Success, Employee Success, and Speed. We're not just any public company – we made history in 2021 by becoming a public benefit corporation (PBC), legally bound to balancing the interests of customers, employees, society, and investors.
As a Work Anywhere company, we support your flexibility to work from home or in the office, so you can thrive in your ideal environment.
Join us in transforming the life sciences industry, committed to making a positive impact on its customers, employees, and communities.
The Role
This is not a traditional curriculum developer role \- please do not apply if you have dabbled with AI agents. In this unique role, we are accepting applications for two different personas:
The AI Solutions Engineer turned Mentor/Coach \- you have an engineering/development background and have become the AI/Technical Trainer to teach learners how AI agents to build and configure agents and AI best practices.
The Technical Curriculum Developer turned AI Builder \- you have a passion for teaching others deep technical topics, and have the curiosity and drive to learn and vibe code agentic solutions/integrations.
If you are one of these profiles and have proven, demonstrable experience \- please apply now!
You'll build the training that teaches customers, partners and Veevans how to use, configure, and implement and integrate our platform — including its Agentic AI capabilities — and you'll build the AI agents that power our demos and hands\-on labs.
You should be able to walk into an unfamiliar product area, understand its architecture and APIs, and within days be building working agent demos and lab exercises around it.
You'll also own and evolve our most technical training courses, the coding\-intensive classes that require real Java and REST API fluency, bringing rigor and firsthand credibility that generalist curriculum developers can't.
What You'll Do
AI Agent Curriculum \& Enablement
Design and build hands\-on training and lab environments that teach technical learners how to build, configure, and deploy custom AI agents on our platform
Build working AI agent demos and reference implementations from scratch to anchor training content and live demonstrations
Translate the practical challenges learners face when configuring or implementing Agentic AI — tool/function calling, context management, prompt design, error handling, guardrails, orchestration — into clear, sequenced learning experiences
Stay current with the agentic AI landscape (frameworks, MCP\-style tool integrations, agent orchestration patterns)
Technical Curriculum Development
Own and maintain our advanced technical courses, including classes that require coding in Java and working with REST APIs
Build and maintain hands\-on lab environments, sample code, sandbox data, and technical exercises that mirror real implementation scenarios
Partner with Product and Engineering to get early access to new features and build courseware alongside General release
Apply instructional design best practices (learning objectives, scaffolding, assessment design, adult learning principles) to technical content without watering down technical accuracy
Cross\-Functional Collaboration
Work closely with Product Management and Engineering to understand agent architecture, APIs, and configuration options as they're being built
Partner with Professional Services, Managed Services and Customer Support to identify pain points and close those gaps with curriculum
Requirements
Bachelor's degree in Computer Science, Engineering, Instructional Design, or equivalent practical experience
Hands\-on experience building, configuring, and deploying AI agents (e.g., using frameworks/SDKs such as LangChain, LangGraph, Anthropic's Claude Agent SDK/Claude Code, or similar)
Practical understanding of core agent concepts: tool/function calling, retrieval\-augmented generation (RAG), context/memory management, multi\-agent orchestration, prompt engineering, and evaluation
Experience with the Model Context Protocol (MCP) or comparable tool\-integration standards is a strong plus
First\-hand experience troubleshooting the real problems agent builders hit — flaky tool calls, context overflow, hallucinated actions, permission/scoping issues — so you can teach learners to anticipate and solve them, not just follow a script
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
3\+ years building technical training, curriculum, or enablement content for a technical audience (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 (e.g., Articulate, Camtasia, Arcade, Vyond, Gemini, Claude or similar) is a plus
Experience with Veeva Vault, or ability to quickly ramp up on, complex enterprise SaaS platforms — including how Veeva Vault is configured and implemented by customers
Self\-directed and comfortable with ambiguity — this role will often be defining the curriculum for capabilities that are still being built
Strong writing and technical communication skills; able to explain complex technical concepts clearly to varied audiences (technical and semi\-technical learners)
Strong presentation and facilitation skills; comfortable leading live demos and workshops
Interviewing with Veeva
We value your time and believe in a transparent hiring process. Here is the process you can expect.
Follow the application process and submit your resume.
Within 3 days, you will receive a link to a personality assessment administered by a third party.
Once you complete the assessment, our team will review your full application package and follow up via email with our decision.
If moving to the interview stage, the process is as follows:
A conversation with the hiring manager
A practical case exercise
A final conversation with our group's Senior Leader.
Once all interviews are complete, the manager will be in touch with a final decision.
Perks \& Benefits
Medical, dental, vision, and basic life insurance
Flexible PTO and company paid holidays
Retirement programs
1% charitable giving program
Compensation
Base pay: $100,000 \- $175,000
The salary range listed here has been provided to comply with local regulations and represents a potential base salary range for this role. Please note that actual salaries may vary within the range above or below, depending on experience and location. We look at compensation for each individual and base our offer on your unique qualifications, experience, and expected contributions. This position may also be eligible for other types of compensation in addition to base salary, such as variable bonus and/or stock bonus.
\#LI\-Remote
\#LI\-Associate
Veeva’s headquarters is located in the San Francisco Bay Area with offices in more than 15 countries around the world.
Veeva is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity or expression, religion, national origin or ancestry, age, disability, marital status, pregnancy, protected veteran status, protected genetic information, political affiliation, or any other characteristics protected by local laws, regulations, or ordinances. If you need assistance or accommodation due to a disability or special need when applying for a role or in our recruitment process, please contact us at talent\[email protected].
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Salary Context
This $100K-$175K range is in the lower quartile for AI Agent Developer roles in our dataset (median: $200K across 33 roles with salary data).
View full AI Agent Developer salary data →Role Details
About This Role
AI Agent Developers build autonomous systems that can reason, plan, and take actions. They design multi-step workflows, tool-use frameworks, and orchestration layers that let LLMs interact with external systems. This is the frontier of applied AI engineering.
Agent development is where the most interesting (and hardest) problems in applied AI live right now. Making an LLM answer a question is straightforward. Making it reliably execute a 15-step workflow that involves calling APIs, reading databases, making decisions, and recovering from errors is an unsolved problem. You're building systems that have to work despite the fact that the underlying model is non-deterministic.
Across the 4,317 AI roles we're tracking, AI Agent Developer positions make up 1% of the market. At Veeva Systems, this role fits into their broader AI and engineering organization.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
What the Work Looks Like
A typical week includes: designing the action space and tool definitions for a new agent use case, debugging why the agent chose the wrong action sequence on a specific input, building evaluation frameworks that test agent reliability across hundreds of scenarios, optimizing the prompt chain for cost and latency, and implementing safety guardrails to prevent the agent from taking destructive actions. The work is equal parts engineering and empirical science.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
Skills Required
Deep experience with LLM APIs and agent frameworks (LangChain, CrewAI, AutoGen). Strong understanding of prompt engineering, function calling, and error handling for non-deterministic systems. Python is standard. Experience with orchestration patterns, state management, and workflow engines adds significant value.
The best agent developers think like systems engineers. They design for failure modes, build observability into every step, and understand that agent reliability is the product. Expertise in evaluation methodology for non-deterministic systems is the differentiator. Can you measure whether your agent works 'well enough'? Can you find the edge cases where it breaks?
Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
Compensation Benchmarks
AI Agent Developer roles pay a median of $240,000 based on 96 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($137K) sits 43% below the category median. Disclosed range: $100K to $175K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Veeva Systems AI Hiring
Veeva Systems has 4 open AI roles right now. They're hiring across AI Agent Developer, AI Product Manager, AI Consultant. Based in Remote, US. Compensation range: $140K - $175K.
Remote Work Context
Remote AI roles pay a median of $180,000 across 1,196 positions. About 15% of all AI roles offer remote work.
Career Path
Common paths into AI Agent Developer roles include Software Engineer, LLM Engineer, Prompt Engineer.
From here, career progression typically leads toward AI Architect, Principal Engineer, Head of AI Engineering.
Build agents. That's the portfolio. Take an open-source agent framework, build something that completes a non-trivial multi-step task, evaluate it rigorously, and document what you learned about reliability, cost, and failure modes. The field is new enough that practical experience counts for more than credentials.
What to Expect in Interviews
Interviews focus on systems thinking and reliability engineering. Expect questions about agent architecture: how you'd design a multi-step workflow with error recovery, how you'd evaluate agent performance, and how you'd prevent agents from taking destructive actions. Coding exercises often involve building a simple agent with tool use and evaluating its behavior across different scenarios. Discussion of safety and guardrails is increasingly common.
When evaluating opportunities: Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.