Engineering Lead

𝗔𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗿𝗼𝗹𝗲
You will own a few of Finrep's product lines outright: the architecture behind them, the two to four engineers building them, and the quality of what reaches customers.
The stack is Python and Go services on Kubernetes, a Next.js frontend, and pipelines that move filings, XBRL, and documents at volume. You make the calls on how those pieces fit, and you are still writing code most weeks.
You also set how this team builds. We use AI heavily in our own development, and we want someone with a real point of view on where that helps, where it quietly costs you, and what has to be true before an agent's output merges.
The bar: Our users are SEC reporting leads, controllers, and audit partners. A wrong number can reach a filing, so every change gets checked against source data and the failure cases we already know about.
𝗪𝗵𝗮𝘁 𝘆𝗼𝘂 𝘄𝗶𝗹𝗹 𝗱𝗼
Own the architecture behind your product lines: service boundaries, the contracts between them, how they degrade under failure, and what reaches customers
Manage two to four engineers: set direction, review code, give feedback that lands, and settle the technical disagreements the team cannot
Design the retrieval and agent pipelines behind our reporting workflows, and the evals that keep them honest as models and prompts change
Make the scaling calls on data: filings, XBRL, and document pipelines where a slow query becomes a support ticket
Own production reliability for your services: Kubernetes, CI/CD, instrumentation, incident response, and the fixes that follow
Define how this team builds with AI: what agents write, what a human reviews, what a test has to prove before anything merges
Hire and ramp engineers as the team grows
𝗪𝗵𝗮𝘁 𝘄𝗲 𝗮𝗿𝗲 𝗹𝗼𝗼𝗸𝗶𝗻𝗴 𝗳𝗼𝗿
4-6 years building production software, with 1-3 years leading or mentoring engineers, formally or not
Strong production Python. Go is a plus, or show us a new language you picked up and shipped production code in
Shipped an LLM-backed system that real users depend on, and measured whether it got better
Owned a service in production: designed it, ran it, and been on the hook when it broke
Current enough technically to lead a design review and make the call when the team is split
You build with AI tooling daily and have a real opinion on where it belongs in the SDLC and where it does not
Clear written communication. You can explain a tradeoff to someone who is not an engineer
𝗪𝗵𝗮𝘁 𝗮𝗱𝗱𝘀 𝗮 𝗯𝗼𝗻𝘂𝘀
Go in production
Kubernetes on AWS, Azure, or GCP at meaningful scale
Data pipelines or storage at a volume where design shows up in the latency graph and the bill
Retrieval systems, evals, or agent orchestration running at scale
Took a product from its first customer through repeated releases
Internal tooling or an SDK that other engineers actually adopted
Open source, or a write-up of a system you built and the decisions behind it
𝗪𝗵𝗮𝘁 𝘁𝗵𝗶𝘀 𝗶𝘀 𝗻𝗼𝘁
Not a management track away from code. You will write code most weeks
Not a role with an architecture handed to you. You propose it, then defend it
Not a place to learn distributed systems from scratch. You need prior experience with partial failures, retries, and data consistency

Work arrangement
Hybrid