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Averity is expanding its engineering team and seeking an experienced, generalist engineer who can own deliverables end-to-end across the stack. The role emphasizes building AI-native features and agentic workflows, with autonomy to discuss problems, propose features, and ship production-ready software.
You will work on data extraction from EHR platforms, analytics, and scalable infrastructure while collaborating with therapists and practice owners as needed.
Our company builds software and operational infrastructure for psychotherapy practices. We help therapists and practice owners understand how their businesses are performing, identify what needs attention, and reduce the administrative work required to run a practice. We're expanding our engineering team as the company grows.
We're looking for an experienced, generalist engineer — someone who can own a deliverable
end-to-end, across the stack, without needing well-defined requirements or close management.
We're also building toward a product where AI sits at the core of how the system works, not
bolted on after the fact — so experience building agentic or LLM-powered features is a strong
You’ll own both the roadmap and the execution for whatever you take on — discussing
problems, identifying opportunities, forming opinions, proposing features, making tradeoffs,
building the product, deploying it, and operating it in production.
Depending on where you land, your work may include:
We use Claude Code and Codex as core engineering tools, and we're looking for someone with
a sophisticated, high-throughput agentic workflow, not occasional AI-assistant use. That might
mean running many agent sessions in parallel, splitting large initiatives into independent
workstreams, or building tooling around agent orchestration, review, and testing.
At the same time, we don't want someone who relies on LLMs for basic reasoning. You should
have developed strong engineering judgment before coding agents were widely available,
understanding how systems work, catching bad assumptions, and navigating hard technical
decisions independently. We're looking for someone who was already an excellent engineer and
has used LLMs to become dramatically more effective.
Our stack: FastAPI, React, PostgreSQL, ECS, RDS, ElastiCache, EC2, Playwright, and GitHub
agent tooling is useful but not required.
This is an individual-contributor role with real scope and influence over the product. It may grow
into technical leadership over time, but that's not a requirement to take it on.