Senior Software Test Engineer

Curative is building the future of health insurance with a first-of-its-kind employer-based plan designed to remove financial barriers and make care truly accessible: one monthly premium with $0 copays and $0 deductibles*. Backed by our recent $150M in Series B funding and valuation at $1.275B, Curative is scaling rapidly and investing in AI-powered service, deeper member engagement, and a smart network designed for today’s workforce.

Our north star guides everything we do: healthcare only works when people can actually use it. That belief drives every decision we make: from how we design our plan, support our members, to how we collaborate as a team.

If you want to do meaningful work with a team that moves fast, experiments boldly, and cares deeply, Curative is the place to do it. We’re growing fast and looking for teammates who want to help transform health insurance for the better.

Summary

We are hiring a Senior Software Test Engineer to help us deliver quickly with the right level of quality. If you're picturing test plans, sign-off gates, and sprint ceremonies, this is not that job. At Curative, every engineer owns what they ship. Your job is to make that possible at speed. A big part of that is our AI agents, which do real operational work in production. We're investing in the evaluation layer to match: eval suites, regression harnesses, and systematic measurement. But the role is not only infrastructure. You'll work directly with business teams, become a domain expert in corners of our business, test the way real users work, and catch the gap between what was asked for and what was shipped. Some days you're writing an eval harness; some days you're hunting a bug an operations teammate can feel but can't pin down; some days you're shaping what gets built next. You'll advise on quality concerns, and you'll jump in and fix things yourself: same day, not next sprint. If ambiguity sounds stressful, this is the wrong role. If moving between code, product, and people in the same afternoon sounds like the best part of the job, keep reading.

How we build

At Curative, AI writes most of the code. Engineers direct it, using agentic AI coding tools as the primary development surface: setting context, making the decisions the AI cannot, and keeping the bar high on what ships. This is not a role for someone who wants to hand-roll every line, nor for someone who will accept whatever the AI produces. We want the engineer in between: fundamentals strong enough to catch a wrong answer fast, discipline to review every diff, and ambition to drive several times the output of a traditional IC.

What you'll own

• The eval platform. Harnesses, datasets, graders, and CI integration that let teams measure agent behavior: task success, tool-use correctness, drift, latency, cost. You'll build it and make it the thing teams reach for because it's useful, not because a process says so.
• Hands-on, exploratory testing. You test the way members, operations teams, and providers actually use the product, end to end, weird paths included, and find what breaks before the real world does.
• Validating we built the right thing. You sit with business stakeholders, understand the real workflow, and catch the gap between what was asked for and what was shipped.
• Domain expertise. You go deep enough on our business that teams pull you in because you understand the workflow, not just the code.
• Production signal and bug hunting. Traces, failure taxonomies, and dashboards that turn "the agent seems off" into a specific finding. In incidents you reproduce the failure, find the root cause, and fix it or hand off a diagnosis so precise the fix is obvious.
• Product judgment when needed. Sometimes there's no PM in the room. You can write the requirement, propose the behavior, make the call, and hand it back gracefully when the right owner shows up.
• Prioritization under chaos. Finite hours, wide surface. You decide where effort goes first, which agents carry the most risk, and which failures are expensive versus merely embarrassing, and you defend that call.

What we're looking for

Foundational skills

• 5+ years in software quality, testing, or engineering with real range. You've written automation and done serious exploratory testing, moving between them as the problem demands.
• Real fluency with LLM evaluation. Golden datasets, LLM-as-judge, programmatic graders, regression suites for prompts and agent loops. You can point to evals that caught real problems.
• Hands-on experience with AI agents and the ways they fail: silent drift, tool misuse, compounding errors.