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- 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.

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- 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

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- 4-6 years building production software, with 1-3 years leading or mentoring engineers, formally or not
- Solid 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

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- 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

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- 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

📌 Engineering Lead (Bengaluru)
🏢 Finrep Ai
📍 Bengaluru