Principal User Assistance Developer

Oracle
1 year ago
Applications closed

Related Jobs

View all jobs

Principal Data Scientist

Senior Data Scientist

Lead Data Scientist - Customer Development

Senior Data Scientist - Fixed-Term Contract

Principal Data Scientist and Machine Learning Researcher

Principal Machine Learning Scientist - Applied Research (UK Remote)

Our customers run their businesses on our platforms and our mission is to provide them with best-in-class compute, storage, networking, database, machine learning, artificial intelligence, security, and foundational services. We seek a top-notch, senior technical writer with deep knowledge and experience in creating technical documentation that include real-world examples and scenarios as well as documenting APIs and SDKs. As a member of the technical content team, you will have significant influence on technical content strategy in all areas, including authoring environments, integration with engineering workflows, automation tooling, and style guide development. You will also collaborate closely with our state-of-the-art user experience team to go beyond traditional forms of product documentation to deliver a ground-breaking overall user experience. At Oracle you can have significant strategic and technical impact by helping to build innovative technical content from the ground up. If you enjoy a challenge and seek to influence your work and working environment, this may be the opportunity for you.

Qualifications

10+ years of experience writing user and developer-focused content or training materials, including guides, tutorials, and white papers. Understanding of cloud concepts and technologies Experience developing API and SDK documentation. Knowledge of REST principles and design. Impeccable written English skills.  Experience developing multimedia assets. Strong team player with outstanding communication, organization, and interpersonal skills. We believe the HOW is as important as the WHAT. A history of fearless hands-on investigation and product use and a strong customer advocate mentality. Comfort with agile, swiftly changing, dynamic software development situations. Ability to learn new technologies quickly. Ability to establish and follow style and usage guidelines. Ability to drive, follow, and evangelize cross-team processes. Familiarity with software localization and accessibility guidelines. Understanding of transformation engines and content management systems. Experience using distributed source code management systems, such as Git. Experience using enterprise-grade bug tracking systems, such as JIRA. Experience and commitment to capturing and maintaining institutional knowledge . A Bachelor’s degree in a writing-intensive field, or significant work experience in startups or fast-paced enterprise technology development environments. Leadership of a significant documentation team effort. Ability to write code samples in Java. Experience developing multimedia assets Knowledge of DITA, XML, CCMS, and authoring tools such as Oxygen XML Editor

#LI-DNI

Career Level -

Deliver accurate customer-facing documentation on time and with a high degree of quality. Collaborate with the user experience team to ensure that technical content — including documentation, multimedia, contextual help, UI text, and other forms of assistance — are discoverable, usable, and pleasing to the customer. Work closely with engineers and product managers as APIs and SDKs are developed to author documentation in real time. Contribute to strategic initiatives around authoring environments, development processes, and automation tooling. Work closely with other members of the technical content team and follow corporate and team style guides to ensure consistency in workflow and writing style. Contribute to design, coordination, and validation of major enhancements to user assistance practices, patterns, processes, and standards. Lead and drive cross-team or cross-organizational projects and initiatives.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.