Software Engineer L2 - Real-Time Pharmacy Platform

Curative is building the future of health insurance with an innovative employer-based plan designed to enhance accessibility. They are hiring a Software Engineer L2 to develop a real-time benefits management platform, collaborating closely with operations specialists and stakeholders to ensure the platform meets user needs and maintains high availability.

Responsibilities:

• The codebase. A full-stack Python + TypeScript application with significant domain complexity. You own code review, architectural decisions, and the quality bar. Most commits will be AI-authored, human-directed, human-reviewed. All of them are yours
• AI leverage. The internal tooling, prompts, skills, and evals that let one engineer operate a service of this scope. You will extend it
• Production — and uptime. This is an always-on service, so production is the heart of the role. You own the cloud infrastructure, deploy pipeline, observability, on-call, and cost — and you design for resilience: failover, monitoring that catches problems before users feel them, and disciplined incident response. Keeping this platform fast and available is one of the most satisfying challenges here
• Operational metrics. You watch how the platform performs for the people who depend on it — not just availability and latency, but workflow completion rates, throughput, time-to-resolution, and the other metrics that tell you whether the software is actually helping end users. You surface what the data shows, propose changes, and close the loop
• Stakeholder relationships. You are the engineer in the room with operations specialists, analysts, and ops leads. You translate their pain into scope, push back when a request won’t solve the real problem, and build trust by shipping reliably
• The roadmap. Co-owning the product plan with operations and product stakeholders. Sequencing work, flagging what is infeasible, proposing alternatives — and sometimes arguing for the thing nobody asked for yet because you are close enough to the problem to see it
• Strategy for your surface. You don’t just execute a roadmap handed to you — you shape it. You see patterns across user feedback, production data, and business goals, and propose what to build next
• Integrations. A growing set of connections to other internal services and external partner and provider systems
• The domain. You will not arrive an expert in this space, but within 90 days you will understand the workflows well enough that every prompt you write is loaded with the right context

Requirements:

• 5+ years shipping production software. Enough reps that you recognize bad code before you can articulate why
• Real fluency in Python and TypeScript. Not 'I can read it' — fluent. You will direct work in both every day
• Strong SQL and relational database fundamentals. You can read a query plan, spot an N+1, and know when a migration is unsafe at scale
• Comfort with operational data. You have built or maintained dashboards, dug into usage metrics to find problems, and used data to argue for or against a product change
• Systems thinking, with a bias toward resilience. Can sketch a service's architecture on a whiteboard, identify the failure modes, design for graceful degradation, and reason about blast radius — because this system is expected to stay up
• Scaling resilient systems. You have designed and operated services that stay fast and correct as load grows — horizontal scaling, caching, queueing and backpressure, idempotency and retries, rate limiting, connection and resource pooling. You know how to find a bottleneck before it becomes an outage, and how to keep a system degrading gracefully instead of falling over under peak demand
• Production cloud experience (AWS, GCP, or equivalent). You have been on-call for something real
• Comfort working directly with non-technical stakeholders. You can run a 30-minute workflow review with an operations specialist, extract the real requirements, and leave them feeling heard — not bulldozed
• Sharp written communication. You will spend more time writing prompts, specs, and PR descriptions than writing code
• You already use Claude Code, Cursor, Codex, or equivalent as your primary development tool — not as a side autocomplete
• You have opinions about how to structure prompts, when to split work into subagents, and how to keep AI output from drifting
• You treat the AI as a junior engineer with infinite throughput: high leverage, zero judgment, needs supervision — so you review every diff and never merge on vibes
• You enjoy building tooling that makes AI more effective on your codebase — skills, evals, fixtures, integrations
• You see AI leverage as what makes it possible for one engineer to own a full product surface and stay close to users — not as a reason to stay heads-down in a terminal
• A portfolio of AI-assisted work — skills you wrote, agents you built, automations you shipped
• Experience being the single owner of a non-trivial service in production