Job Description
Want to build the systems that make AI agents actually work in production?
Most agents fail outside controlled environments, not because the models are weak, but because the systems around them can't represent how real work happens.
This team is building that missing layer...
Their platform sits inside enterprise workflows, capturing how tasks are executed across tools, then structuring that data so models and agents can actually use it. Real operational context, not synthetic benchmarks.
As a Full Stack Engineer, you'll focus on the backend and product systems that make this usable in production.
You'll design workflow data models, build high-throughput pipelines, and ship full-stack features used by real customers. This sits across distributed systems, data engineering, and LLM integrations.
Tech stack includes TypeScript (NestJS, React, Vite, TanStack), PostgreSQL, and AWS/GCP, with OpenAI and Anthropic models integrated into core systems.
You'll join a small, highly technical, Accel-backed team that's already post-revenue and scaling with enterprise customers. This isn't speculative infrastructure, it's being used.
Experience with Python pipelines, Terraform monorepos, or Rust/Swift is useful, but not essential.
What matters is your ability to build systems that hold up in real-world complexity.
San Francisco (on-site)
$160K-$280K base + equity + additional comp
If you're interested in building the layer that makes AI agents usable, this is where that work is happening.
All applicants will receive a response.
