Technical Writer - 14709

Position: Technical Writer

Working Hours: Monday to Friday, 5:00 AM - 2:00 PM, Pacific Time

About the role: 

The clients company helps candidates practice with real interview questions. They’re looking for a self-directed Technical Writer/Content Editor to maintain and improve their interview-question library— keeping questions accurate, fresh, well-tagged, and genuinely engaging to solve. You don’t need to be a deep expert in every domain, but you do need enough Python/SQL fluency and product sense to know when something is correct, unclear, or outdated and to fix it quickly.

Responsibilities:

• Own the question bank. Review, edit, and publish interview questions and solutions across Data Science, Analytics, ML/AI, and Data Engineering categories.
• Raise quality. Rewrite unclear prompts/solutions, standardize difficulty and tags, add hints, edge cases, and testable I/O where relevant.
• Use LLMs as a power tool. Prompt LLMs to draft outlines, generate variants, sanity-check solutions, and catch inconsistencies, then verify and polish.
• Keep content fresh. Triage what to update or retire based on product direction, user feedback, internal pool of interview experiences, and performance metrics (answer rate, saves, time-to-completion).
• Ship without hand-holding. Plan your own weekly pipeline; identify gaps; propose new questions/collections aligned with product strategy.
• Tag & structure. Ensure consistent taxonomy (topic, subtopic, difficulty, company/role), metadata, and searchability.
• Partner with Product. Align priorities with the roadmap and surface insights from learner behavior.

Requirements:

• 2+ years of experience relevant to the role
• Strong technical writing and synthesizing skills.
• Strong AI skills and knowledge of context engineering, prompt engineering, and building AI agents and workflows
• Working Python (basic → intermediate): data types, control flow, functions, simple algorithms; able to read/validate solutions.
• Working SQL (basic → intermediate): SELECT/JOINs, GROUP BY, CASE, window functions at a minimum; can sanity-check queries and expected outputs.
• LLM fluency: comfortable crafting prompts, using tools to draft/verify, and knowing where human review is essential.
• Editorial judgment: can spot ambiguity, leakage, or trivia; can rewrite to be clear, fair, and interview-realistic.
• Self-management: you plan your week, triage the backlog, communicate status, and ask for direction only when it truly changes scope.
• Tool comfort: Markdown and basic version control (or willingness to learn); can work from a content CMS/workboard.

​​​​​​​ Nice to have

• Experience interviewing or being interviewed for data/ML/analytics roles
• Light pandas or NumPy familiarity for Python questions
• Understanding of SEO basics for educational content
• Experience with tagging taxonomies and content QA workflows