Developer Relations Engineer

How do you turn a decades-old dataset into an industry-leading medical coding agent? Teach an AI receptionist to book appointments in Spanish? Automatically generate working data connectors from API docs? Build agents that write, test, and deploy their own software packages?

Fractional AI is focused on putting frontier AI to work. We're a group of veteran Silicon Valley builders who care deeply about getting complex AI systems built right, with strong conviction about what makes them succeed.

We're backed by Anthropic, Blackstone, Hellman & Friedman, Goldman Sachs, General Atlantic, Leonard Green & Partners, Apollo Global Management, GIC, and Sequoia Capital.

Fractional AI is widely regarded by practitioners as one of the best teams at AI implementation in complex scenarios. Our brand awareness among top-tier engineers hasn't kept pace with our output. On May 20, we became the founding team of Anthropic's new AI Services Business and it's the right moment to bring in our first Developer Relations Engineer to build a lasting engineering brand.

You'll be embedded in the engineering team — reading code, sitting in architecture reviews, talking to clients — and translating that work into content, community, and presence that engineers actually respect. You're not a marketer who covers engineering. You're an engineer who happens to be exceptional at telling the story of the craft.

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  Write and publish technical content — blog posts, project teardowns, HN writeups — drawn from what the team is actually building

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  Build Fractional's presence on channels where strong engineers spend time: Hacker News, technical podcasts, conferences, and niche communities

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  Run high-signal community touchpoints: dinners, workshops, small events where top engineers encounter Fractional in a non-transactional context

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  Drive open source contributions and external projects that reflect Fractional's engineering caliber

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  Build partnerships with complementary technical brands — co-sponsoring events, co-publishing content, cross-pollinating communities

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  Feed signal back to engineering leadership: what practitioners are excited about, skeptical of, building toward
  

• 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.
  

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. We think you'll find it refreshing if you've seen how most companies approach AI.

A typical engineer here ships two to three products per year and learns from dozens more. In this role, you'll have direct visibility into that full portfolio — which means a richer, more credible voice than any DevRel who's been handed a press release.

• Overdeliver: We are writing the playbook on how to create enterprise value with LLMs, and building our reputation as the world's best applied AI team.

• Overuse AI: We go out of our way to experiment with the latest tools and share what we learn with our teammates — building a culture at the frontier.

• Over "engineer" the culture: For every big decision, we ask "would this make Fractional a better or worse place for our team?"