Software Engineer L2 - Finance & Accounting Platform

Curative is hiring a forward deployed software engineer to own its Finance and Accounting platform for health-plan financial operations. The role spans building and operating the data-intensive application, ensuring financial correctness, developing AI agents to automate support and billing work, and partnering with F&A and product stakeholders.

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
• Agents that do the work. You will design and ship AI agents that handle support and billing issues and automate the manual processes the F&A team runs by hand today — turning recurring, tedious work into software that runs itself. This is some of the highest-leverage work on the platform, and it’s yours to own end to end
• The data. This platform lives and dies on its data — moving it from many sources, transforming it correctly, and keeping it trustworthy. You own the pipelines that feed it and the checks that catch a bad number before anyone downstream sees it
• Financial correctness. The numbers this platform produces have to be right. You own the logic and the safeguards that make the output something the business can rely on and stand behind
• Production. Cloud infrastructure, deploy pipeline, observability, on-call, incident response, and cost — including the data jobs the F&A team depends on running on schedule
• Sensitive data. This platform touches both PHI and financial information. You own handling it responsibly, with data-privacy discipline baked in rather than bolted on
• Operational metrics. You watch how the platform performs for its users — not just uptime, but whether the numbers reconcile, how much manual work the software is or isn’t eliminating, and where the data says something is off. You surface what the data shows, propose changes, and close the loop
• Stakeholder relationships. You are the engineer in the room with accountants and F&A 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 F&A 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 stakeholder feedback, the data, and business goals, and propose what to build next
• Integrations. A growing set of connections to internal services and third-party financial systems that this platform reads from and writes to
• The domain. You will not arrive an expert in health-plan finance, 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
• Real fluency in Python and TypeScript
• Strong SQL and relational database fundamentals
• Experience building data-intensive applications
• A correctness mindset
• Systems thinking
• Production cloud experience (AWS, GCP, or equivalent)
• Comfort working directly with non-technical stakeholders
• An interest in working with financial data
• Sharp written communication
• 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 review every AI-generated diff
• You treat the AI as a junior engineer with infinite throughput: high leverage, zero judgment, needs supervision
• 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
• Experience with data-intensive or financial systems — data platforms, analytics, billing, payments, or reporting