Client is seeking a long-term partnership with a deeply technical writer who is familiar with AI infrastructure and usage, particularly within engineering workflows. The ideal writer will not only understand the nuances of AI tools and LLMs, but will also bring practical, practitioner-level insight into topics such as inference costs, prompt retention, and caching.
This writer must be able to generate content that goes beyond surface-level explanations—focusing on detailed problem-solving, deep dives into infrastructure, and strategic value demonstrations for technical audiences.
Scope- Duration: 3-month initial commitment with potential for longer-term engagement
- Weekly Commitment: Approx. 10 hours/week (45 hours/month)
- Content Volume: 2–4 blogs per month
- Flexibility: Writer may also contribute to guides, webpages, or other technical collateral
- Produce technical blog posts, guides, and web content tailored to AI engineers, enterprise developers, and AI-first startups
- Work collaboratively with client’s internal engineers to extract insights and convert them into publishable content
- Participate in occasional meetings or interviews to gather content-specific context
- Provide strategic input into content topics aligned with middle-of-the-funnel goals
- Deliver high-quality, thoroughly researched drafts with minimal editorial overhead
- Deep familiarity with AI, LLMs, and related infrastructure (e.g., caching, inference, latency management)
- Demonstrated experience producing technical content for practitioner-level audiences
- Ability to translate complex technical topics into clear, accessible, and insightful articles
- Preferred: Experience working in or with AI-first startups or bottom-up AI initiatives inside large enterprises
- Strong editorial discipline with minimal need for hand-holding
Client is a two-year-old developer-focused company that provides API access to a wide range of language models. It serves highly technical customers across three main segments: indie hackers, enterprise companies, and AI-first startups. The company is focused on optimizing both internal and external AI use cases with a deep emphasis on performance, cost-efficiency, and technical administration.
