Staff Product Engineer

DaParrot Ltd; Deutschland; Vor Ort; EUR 70.410 - 88.013; Vollzeit

Benefits dieser Stelle

Competitive salary

Work from anywhere

High ownership and autonomy

Zusammenfassung

DaParrot Ltd is seeking an engineering lead to drive initiatives with AI technologies. You'll take charge of the technical architecture, oversee implementation quality, and work closely with product managers and designers.

Your role is to ensure successful outcomes measured by metrics, while leveraging autonomy in decision-making. The ideal candidate has strong skills in AI coding and experience leading tech projects.

The position offers a competitive salary of $80,000–$100,000 and allows for a high degree of ownership and autonomy.

Qualifikationen

• Proficient in AI coding with tools like Claude Code, Cursor, and Codex.
• Experience at a lead level and making impactful decisions.
• Ability to measure success based on metrics and outcomes.

Aufgaben

• Define the technical architecture and approach for initiatives.
• Ensure high-quality implementation and production readiness.
• Collaborate with PMs and designers to shape product outcomes.

Kenntnisse

AI coding

Technical architecture

Cross-functional collaboration

Outcome measurement

Tools

PHP

TypeScript

React

Jobbeschreibung

The Role

You’re the engineering anchor of an initiative — working as part of a tight team with your PM and designer, and alongside engineering peers on adjacent initiatives. You have a hand in the full lifecycle: shaping the problem, deciding the technical approach, directing AI agents to implement much of the code, shipping to production, and — with your team — owning the outcome.

You’re measured by impact, not by lines of code merged. When an agent can ship something safely, your job is to make sure it’s done right and the metric moves. When the work calls for careful, hand‑written code in a sensitive area, you write it yourself.

What Makes This Role Exciting

• You ship end‑to‑end. From problem‑framing through production to the post‑launch metric review — you see the whole arc and own the result with your team.
• You work as a true product partner. You sit at the table with PM and design, bringing engineering judgment to product calls and product sense to engineering calls.
• You get real autonomy — with the right checkpoints. You make most technical calls yourself, with architect review on significant architectural decisions and fast input from peers.
• You operate at a staff bar. You’re trusted to make the call, ship the hard thing, and stand behind the outcome.

What You’ll Own

• The technical approach — architecture, data model, integration choices, rollout plan, observability, and rollback strategy for your initiative.
• Implementation quality — the prompts, guardrails, evals, tests, and review loop that let agents ship safe, correct, production‑ready code.
• Cross‑functional partnership — daily working contact with your PM (scope, tradeoffs) and designer (UX decisions, in‑tool prototyping), regular collaboration with engineering peers, and weekly check‑ins with your EM.
• The initiative outcome — the metric the initiative was set up to move. With your PM, you present results 2–4 weeks post‑launch and share the “did it work” answer.
• A high bar for what ships — production correctness, security, performance, observability, and the experience for customers and pros.

Problems to Solve

• Leading AI agents at a staff‑level quality bar.
• Owning decisions with high autonomy.
• Shipping outcomes, not features.

What Success Looks Like (Year 1)

• Initiative outcomes hit — You’ve shipped 3–4 initiatives end‑to‑end, and at least two clearly moved their metric.
• Agent workflow that travels — The prompts, evals, and review loop you built are picked up by peers on other initiatives.
• Faster cycle time — Median time from problem‑framing to first production rollout on your initiatives is meaningfully shorter.
• Quality holds — No customer‑ or pro‑facing regression traceable to agent‑authored code that slipped through your review.
• Visible leverage — Peers point to artifacts you left behind — runbooks, evals, agent workflows, post‑launch write‑ups.

Requirements

• AI‑native. Claude Code, Cursor, Codex, or equivalent are how you ship today — daily, on production work.
• Operating at a lead level. Whatever your current title, you’ve been the person making the call, shipping the hard thing, and standing behind whether it worked.
• Outcome‑driven. You measure your week in “did the metric move” and “did the experience get better.”
• A strong horizontal partner. You hold your own with a strong PM and designer, and you collaborate well with engineering peers.
• Decisive and documented. You make architecture, data‑model, and rollout calls, write them down, get fast input, and move.
• A force multiplier. Your impact compounds beyond your own initiative because you leave reusable artifacts behind.
• Customer‑ and pro‑minded.
• You don’t need every box checked. You need deep skill in at least one of our stacks plus credible production experience with AI coding agents.

Tech You’ll Touch

• AI agents — Claude Code, Cursor, Codex, internal agent stack, MCP servers, evals tooling.
• Backend — PHP/Laravel.
• Frontend — TypeScript/React/React Native (customer & pro apps, web and mobile).
• Data — Redshift, dbt, Segment, Airflow.
• Infra — AWS, Datadog, Sentry, GitHub Actions.
• Documentation & process — Brain (Claude Code skills + docs repo), Confluence, Jira.

Benefits

• Competitive salary of USD $80,000–$100,000 annual base.
• Work from anywhere.
• High ownership and autonomy.
• Fast‑moving team that loves to build, learn, and grow.