Embedded in the engineering team, translate complex AI implementation work into respected technical content, community presence, and open source contributions that build Fractional's engineering brand.
Salary not listed
On-siteDeveloper Relations
About the role
What You'll Do
Write and publish technical content — blog posts, project teardowns, HN writeups — drawn from what the team is actually building
Build Fractional's presence on channels where strong engineers spend time: Hacker News, technical podcasts, conferences, and niche communities
Run high-signal community touchpoints: dinners, workshops, small events where top engineers encounter Fractional in a non-transactional context
Drive open source contributions and external projects that reflect Fractional's engineering caliber
Feed signal back to engineering leadership: what practitioners are excited about, skeptical of, building toward
What You Bring
Strong engineering foundation. You've shipped software and cared about doing it right. You understand why good system design matters and can have a credible technical conversation with a senior engineer about AI architecture, eval design, or production tradeoffs.
Exceptional writing. You write with clarity and specificity. You know the difference between content that earns attention and content that fills a feed. You've written things engineers have actually read and shared.
Taste for what resonates technically. You have a feel for the developer zeitgeist — what practitioners find credible, what reads as hype, what makes an HN post land versus get flagged.
High ownership mindset. You jump in without instruction, embrace a "no job too big, no job too small" mindset, and want to shape strategy and culture from day one.
Low ego, high integrity. You help others and ask for help. You hold a high bar for honesty, with yourself and your team.
Engineering at Fractional
We're opinionated about what works in production, and we write about it — from why most eval setups fail by collapsing everything into a single score, to why defaulting to chat interfaces limits AI's impact.
We have a distinct approach to building AI systems: applying standard software engineering discipline to the non-deterministic world of frontier AI. We design systems around testable hypotheses, curate durable datasets, and ensure what we ship keeps working long after we've handed it over.
After shipping 30+ AI products, we have strong opinions on what makes AI products succeed and how to get them into production.
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