Software Engineer L2 - Finance & Accounting Platform

We use agentic AI coding tools as the primary development surface.

Most engineers here routinely runs multiple agents in parallel — one implementing a feature, one resolving review comments, one chasing down a flaky test.

The engineers job is to set context, make the decisions the AI can't make, and keep the bar high on what ships.

This is not a role for someone who wants to hand-roll every line.

It is also not a role for someone who will accept whatever the AI produces.

We are looking for the engineer in between: strong enough fundamentals to catch a wrong answer in a few seconds, disciplined enough to review every diff, and ambitious enough to drive several times the output of a traditional IC.

Strong systems and architecture thinking is important, as is product taste.

This is a fully remote position

What you'll own

• 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.

What we're looking for Foundational skills (non-negotiable)

You need these because you are the last line of defense on what the AI produces.

The bar is not "can write it from scratch in an interview" - the bar is "can read a 400-line AI-generated diff and spot the subtle bug in 90 seconds." In this domain, that bug is often a number that’s quietly wrong.

• 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.
• 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, and reason carefully about the joins and aggregations that decide what a number ends up being.
• Experience building data-intensive applications. You have built systems that move, transform, and reconcile meaningful volumes of data — ETL/sync pipelines and the interfaces on top of them — and you care about getting the data right, not just moving it.
• A correctness mindset. You have built systems where the output has to add up, and you instinctively reach for the checks, invariants, and audit trails that prove a number is right rather than just plausible. You are comfortable with the idea that “close enough” is not close enough.
• Systems thinking. Can sketch a service’s architecture on a whiteboard, identify the failure modes, and reason about blast radius.
• 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 accountant, extract the real requirements, and leave them feeling heard — not bulldozed.
• An interest in working with financial data. You don’t need a finance background, but you should be genuinely interested in the problem space — financial data, the systems that produce it, and the satisfaction of making the numbers come out right.
• Sharp written communication. You will spend more time writing prompts, specs, and PR descriptions than writing code.

Note: prior healthcare or finance experience is not required.

We care far more about your track record building and operating data-intensive systems where correctness matters — any industry counts.

What we do look for is an interest in working with financial data and the discipline that comes with it.

AI-first working style (also non-negotiable)

• 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 do not merge on vibes.
• 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.

Strongly preferred

• 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.

Why this role Healthcare is one of the highest-leverage places software can make a difference, and the money side of a health plan is where a lot of that leverage lives.

We are a company where a single engineer can own the platform that runs it.

The scope is large, the data is real, the correctness bar is high, and the operating model — AI-first, human-directed, shipped daily — is the one you have been waiting for.

Your day might span sitting in on an F&A working session, debugging why two systems disagree on a number, building an agent to take a manual process off someone’s plate, demoing a new workflow to an F&A lead, or setting the technical strategy for your platform.

If you have been looking for a role where you own the full loop — problem discovery through production — where working with data and getting the numbers exactly right actually matters, and where AI-first isn’t a buzzword but the actual way work gets done, this is it.