Location: Remote (Worldwide)
Type: Full-time
Level: Junior to Mid-level (2 – 4 years experience)
Reports to: Leadership team
Clyro is the Agent Kernel — the intelligent infrastructure layer that makes AI agents production-ready. We provide runtime governance for AI agents: loop detection, cost bounds, step limits, and business logic guardrails that prevent failures before they happen.
We're post-launch with early users, a live PLG funnel, and growing developer attention. AI agent deployment jumped from 11% to 42% in a single quarter — but 80% of organizations are experiencing risky agent behaviors. We've built the reliability infrastructure this market needs, and now we're scaling the go-to-market engine around it.
We've already built momentum , a library of published technical articles, an active content pipeline, a rolling editorial calendar, SEO keywords mapped, and a content quality pipeline designed. What we don't have is someone dedicated to sustaining that momentum and scaling output.
You'll own the content-to-distribution pipeline end-to-end: take drafted articles through quality review, optimize for SEO, publish to our Ghost blog, distribute via newsletter and social media, and measure what's working. Then you'll build the engine that produces 2+ pieces per week sustainably.
This is a ground-floor role — pre-revenue, post MVP. You'll have direct access to the leadership team, real influence on how Clyro shows up publicly, and meaningful ownership from day one.
Own the end-to-end quality pipeline from draft through SEO/AEO optimization, editorial review, and publication
Manage the editorial calendar (13-week rolling schedule)
Ensure articles meet Clyro's voice and messaging standards (technically credible, no fluff)
Coordinate with the leadership team on content priorities
Optimize content for target keywords and search intent
Track rankings, organic traffic, and performance using tools like Plausible and Microsoft Clarity
Identify content gaps based on search data and competitor analysis
Improve landing page copy in collaboration with the tech team (Framer)
Launch and manage the Clyro newsletter (Beehiiv)
Build and segment the email list (pre-launch milestone: 500 subscribers)
Write newsletter editions that drive engagement and product interest
Track open rates, click-throughs, and list growth
Create LinkedIn posts and Twitter threads to distribute content
Repurpose articles into bite-sized social content
Coordinate with the DevRel teammate on messaging and timing
Monitor engagement and iterate on formats
You’ve published content in a B2B SaaS or developer tools context (including personal or freelance work)
You understand SEO fundamentals (keyword research, search intent, on-page optimization) and have used tools like Ahrefs, Semrush, or Clearscope
You can take rough drafts and turn them into polished, publishable content without losing technical depth
You use AI tools (Claude, ChatGPT, etc.) to accelerate workflows while applying strong editorial judgment
You can write in a technically credible, clear, and engaging voice
You are self-directed and comfortable working in a fast-moving, early-stage environment
Familiarity with AI/ML concepts (LLMs, agents, LangChain, etc.)
Experience with Ghost, Beehiiv, Framer, or Plausible
Experience at a pre-launch or early-stage startup
Understanding of developer audiences and content expectations
Experience marketing technical infrastructure, AI, or compliance-related products
Existing content momentum: published articles, draft pipeline, and editorial calendar
Clear positioning, personas, and content strategy
Direct access to the leadership team
AI-augmented workflows integrated into the content process
High ownership with minimal bureaucracy
Please send:
A brief note on why this role interests you
1–2 writing samples (B2B/technical content preferred)
A short editorial critique (3–5 sentences) of the paragraph below what you’d change, keep, and why:
Observability tools are architecturally designed to record, not to intervene. They sit alongside the execution pipeline, receiving events as they happen, storing them for later analysis. They do not sit in the execution pipeline with the authority to stop it. Consider three real-world failure patterns where observability was present but damage still occurred: The $47K Loop. An autonomous multi-agent system entered a retry spiral over an unsolvable edge case and ran for eleven days, accumulating $47,000 in API costs. The system had monitoring. Cost alerts were configured at the account level a monthly budget alarm at $5,000 that was designed for normal operations. The agent's status logs