Work with founders, product, and design at the whiteboard stage, before anything is written down, and help decide what's worth building. * Build the AI surfaces of the product; prompt and agent ...
Work with founders, product, and design at the whiteboard stage, before anything is written down, and help decide what's worth building. * Build the AI surfaces of the product; prompt and agent ...
Weekday Ai Prompt Writer information
What is a Weekday AI Prompt Writer?
Weekday AI Prompt Writers are professionals who create, refine, and optimize prompts for artificial intelligence (AI) systems, particularly for applications that require natural language processing, such as chatbots, virtual assistants, and content generation tools. Their role involves understanding both the technical and creative aspects of prompt engineering to ensure AI outputs are accurate, engaging, and user-friendly. They often collaborate with engineers, product teams, and content creators to develop effective prompts that align with business objectives. By crafting and testing prompts, they help improve the reliability, usefulness, and safety of AI interactions.
What are the key skills and qualifications needed to thrive as a Weekday AI Prompt Writer?
To thrive as a Weekday AI Prompt Writer, you need strong language skills, creativity, and a deep understanding of AI prompt engineering, often supported by experience in content writing or linguistics. Familiarity with AI platforms, prompt testing tools, and best practices for generative AI systems is typically required. Excellent communication, attention to detail, and adaptability are crucial soft skills for crafting effective prompts and collaborating with technical teams. These abilities ensure the delivery of high-quality, clear, and efficient AI-generated outputs that meet user and business needs.
How does a Weekday AI Prompt Writer typically collaborate with engineers and data scientists to improve AI-generated content?
As a Weekday AI Prompt Writer, you will frequently work alongside engineers and data scientists to refine and optimize prompts for AI models. Collaboration often involves sharing feedback on how AI responds to your prompts, discussing desired outcomes, and brainstorming ways to enhance accuracy and relevance. Regular meetings and feedback loops help ensure that the models are aligned with project goals, and you may be asked to test new features or provide insights on user interactions. This cross-functional teamwork not only sharpens your technical understanding but also opens up opportunities for growth into roles like prompt engineering or content strategy.
What is the difference between Weekday Ai Prompt Writer vs Content Writer?
| Aspect | Weekday Ai Prompt Writer | Content Writer |
|---|---|---|
| Required credentials | Basic writing skills, familiarity with AI tools | Writing degrees or experience often preferred |
| Work environment | Remote, tech-focused companies | Varies; remote or on-site, diverse industries |
| Employer and industry usage | Tech startups, AI companies | Media, marketing, publishing |
| Search and comparison intent | Understanding AI-specific writing roles | General content creation roles |
The Weekday Ai Prompt Writer focuses on creating prompts for AI models, requiring familiarity with AI tools and basic writing skills. Content Writers produce a wide range of written content across industries, often with formal writing credentials. While both roles involve writing, the AI prompt writer specializes in AI-related tasks, whereas the content writer has broader content creation responsibilities.
Are weekday AI prompt writers in demand?
Weekday AI prompt writers are increasingly in demand as companies seek to improve AI interactions and content generation. The role often requires strong writing skills and familiarity with AI tools like language models, with opportunities available in tech, marketing, and content creation sectors.
How to become a Weekday AI Prompt Writer?
To become a Weekday AI Prompt Writer, develop strong writing and communication skills, gain familiarity with AI language models and prompt engineering, and build a portfolio of example prompts. Relevant experience in AI, machine learning, or related fields can be beneficial, and understanding the specific platform or company's guidelines is important.
Full-time
Re-posted 15 days ago
Key responsibilities
Close incoming platform tickets from Shared Services by triaging, diagnosing, and shipping fixes.
Identify patterns in reported issues and address systemic gaps to improve platform reliability.
Own the development and maintenance of features, including problem framing, design, implementation, and follow-up.
Job description
Location: Europe or South America (remote)
Team: Engineering
Reports to: Head of Engineering
About Extenteam
Extenteam is the AI-driven operations platform for short-term rental property management, headquartered in Miami and founded in 2021. Our platform, Shared Services, handles guest communication and daily operational workflows for 80,000+ properties by pairing an AI orchestration layer with a shared-services team of hospitality-trained specialists, so no guest inquiry goes unanswered, day or night, and no property manager has to staff for the 2am cancellation themselves.
We're industry-only: every workflow, integration, and agent we hire is built around property management specifically, not bolted on from a generalist platform. As we push more of that platform toward AI-led automation and self-serve tools, the software our own Shared Services team works in every day has to keep pace, that's this role.
Why This Role Exists
Shared Services' guest communication runs on two things: an AI layer that handles as much of a conversation as it safely can, and a shared-services team of hospitality-trained agents who catch what the AI shouldn't touch alone. Every day, that team hits walls in the platform they use to do the work; bugs, missing tooling, workflows that don't match how a busy overnight shift actually runs. Some of that is a quick fix. Some of it is a signal that the platform is failing at scale, and by the time it reaches Engineering it's already cost real client trust.
We don't have a layer of PMs pre-chewing every one of those signals into a spec. We're hiring an engineer who can sit close to Operations, tell the difference between a one-off bug and a systemic gap, and ship the fix with no handoff required.
The Role
You'll report to the Head of Engineering. Priorities are set jointly with the Head of Operations, who owns the operational signal driving what gets built. You'll do two things:
About Extenteam
Extenteam is the AI-driven operations platform for short-term rental property management, headquartered in Miami and founded in 2021. Our platform, Shared Services, handles guest communication and daily operational workflows for 80,000+ properties by pairing an AI orchestration layer with a shared-services team of hospitality-trained specialists, so no guest inquiry goes unanswered, day or night, and no property manager has to staff for the 2am cancellation themselves.
We're industry-only: every workflow, integration, and agent we hire is built around property management specifically, not bolted on from a generalist platform. As we push more of that platform toward AI-led automation and self-serve tools, the software our own Shared Services team works in every day has to keep pace, that's this role.
Why This Role Exists
Shared Services' guest communication runs on two things: an AI layer that handles as much of a conversation as it safely can, and a shared-services team of hospitality-trained agents who catch what the AI shouldn't touch alone. Every day, that team hits walls in the platform they use to do the work; bugs, missing tooling, workflows that don't match how a busy overnight shift actually runs. Some of that is a quick fix. Some of it is a signal that the platform is failing at scale, and by the time it reaches Engineering it's already cost real client trust.
We don't have a layer of PMs pre-chewing every one of those signals into a spec. We're hiring an engineer who can sit close to Operations, tell the difference between a one-off bug and a systemic gap, and ship the fix with no handoff required.
The Role
You'll report to the Head of Engineering. Priorities are set jointly with the Head of Operations, who owns the operational signal driving what gets built. You'll do two things:
- Close incoming platform tickets from Shared Services. Agents, Team Leads, and Operations report issues daily; quick fixes, workflow bugs, configuration problems. You triage, diagnose, and ship.
- Find the pattern and fix it at the source. When multiple agents report the same friction, that's not a ticket, it's a product problem. When a client complaint traces back to repeated agent failures, you ask why the platform is allowing it, and you close that gap for good.
Every ship goes through the same process as any other engineer's here: product filters for coherence, design filters for UX consistency, standard code review. This role works inside those guardrails, not around them.
What You Will Do
What You Will Do
- Own features end to end; problem framing, design, backend, frontend, instrumentation, rollout, and the follow-up fixes nobody filed a ticket for.
- Work with founders, product, and design at the whiteboard stage, before anything is written down, and help decide what's worth building.
- Build the AI surfaces of the product; prompt and agent architecture, tool calling, retrieval, guardrails, and the human-in-the-loop escape hatches that make automation safe to ship.
- Build and maintain evals. Treat "does this actually work" as an engineering artifact with a regression suite, not a vibe check before launch.
- Watch real usage. Session replays, logs, transcripts, support tickets, and customer calls. Bring back what you learn as shipped changes, not as a document.
- Own the details that make software feel good; latency budgets, token cost, empty states, error copy, loading behavior, keyboard paths. These are part of the feature, not a separate polish phase.
- Cut scope and kill things. Argue a feature is wrong before you build it well.
- Compound the team's velocity; CI, preview environments, internal tools, seed data, debugging surfaces. Leverage counts as product work.
What This Role Is Not
- Not a ticket queue firefighter. That's other roles on the Operations side.
- Not a shadow engineering team. You report to and work within Engineering.
- Not an independent operator building outside the platform. Everything you ship goes through product.
Anti-Signals
- You want a ticket fully spec'd before you'll touch it
- You treat "why does this keep happening" as someone else's question to answer
- You measure your work by whether you closed the ticket, not whether the pattern stopped
- Your AI/LLM experience is prompting a demo - never held to a reliability bar with a real agent depending on it at 2am
Required Experience
- 4+ years of full stack (stronger on the BE) software engineering experience shipping production enterprise software
- Direct experience building internal tools, agent-facing platforms, or operational systems
- Product mindset: comfortable scoping problems, asking the right questions, and communicating/prioritizing tradeoffs
- Track record of shipping fast while working inside a product and design process
- Experience working asynchronously with distributed teams
Required Technical Skills
- Strong fluency in TypeScript. We currently use:
- Next JS
- NestJS
- TypeORM with Postgres
- BullMQ
- Comfortable with agentic coding tools (Claude Code, Cursor, Replit Agent)
- API integration experience (REST, webhooks, third-party SaaS APIs)
- Prompt engineering experience with production AI systems (OpenAI, Anthropic, or similar)
Strongly Preferred
- Experience building tools for contact center, customer support, or operations teams
- Short-term rental, hospitality, or property management domain knowledge
- Track record of deploying AI agents in production
How You'll Work
- Reports to the Head of Engineering
- Priorities set jointly with the Head of Operations, based on operational signal
- Product decisions filter through the Head of Product
- Design decisions go through our design team
- Weekly syncs with Engineering, Operations, and Product
- 5 hours of overlap with Miami time (Eastern), minimum, daily
Compensation
Base range is $70-105K USD depending on location and experience.