New comment by akkio in "Ask HN: Who is hiring? (September 2026)"
- Status
- Open
- Remote policy
- Remote
- Employment type
- Not stated
- Salary
- Not stated
- Tech
- pythontypescript
- Source
- hn-whoishiring
- First observed
- 2026-09-03 19:17 UTC
- Last seen
- 2026-09-03 19:17 UTC
- Source claims posted
- 2026-09-03 18:14 UTC
- Consecutive misses
- 0 of 10
What the posting says
Akkio | Senior Software Engineers — FDE, Full-Stack, Backend | US (Fully Remote) | Full-time | $160k–$240k + equity | https://www.akkio.com/jobs
Akkio builds the AI platform the world's largest media agencies (Havas, Horizon Media, and others) use to run campaign workflows in production: audience building, media planning, measurement, and campaign analysis. Agentic workflows plus traditional ML, deployed on-premises inside agency cloud environments, directly on top of their data. We're ~50 people, past PMF, well funded, and growing revenue quickly.
We build agentically by default. Every engineer directs coding agents daily, and we're actively rebuilding our SDLC around that — not piloting it, not debating it. If you've felt that shift and want a team that's all the way in, that's us. We also run flat, so "senior" means ownership, not management layers.
Three roles, all $160k–$240k + equity:
* Forward-deployed engineer (FDE) — Python, TypeScript, true generalist. You embed with agencies whose systems steer billions in media spend and build whatever the problem needs: integrations, agent workflows, backend services. What you build in the field becomes product. Regular travel.
* Full-stack (web) — Vue.js, TypeScript, Node.js. You've run projects, guided architecture, and survived framework upgrades and large refactors. You care about the experience analysts live in every day.
* Backend — Python. Interesting work in at least two of: LLM systems and code generation, statistics, traditional AI/ML, large-scale data processing, distributed systems.
Details and application: https://www.akkio.com/jobs
All candidates must be authorized to work in the US.
Quality
- x Salary range stated weight 35%
- + Remote policy stated weight 20%
- x Location stated weight 15%
- + Organisation stated weight 15%
- + Publication date stated weight 15%
Not enough history yet to judge honesty signals.
Timeline
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#555212 2026-09-03 19:17 UTCPublished