Senior Product Engineer, AI-native

This is a fully remote position, open to applicants in Brazil, +1 more country.

📋 Description

• Take full ownership of product and platform projects from inception to customer-facing features.

• Transform briefs into detailed specifications that encompass user requirements, acceptance criteria, technical plans, costs, security measures, and instrumentation.

• Architect straightforward, scalable systems and document essential architectural decisions.

• Coordinate multiple coding agents concurrently, utilizing pertinent context, skills, rules, repository cards, and internal MCP servers.

• Review outputs from agents and create Playwright and unit tests.

• Successfully navigate pull-request and release verification processes.

• Launch features behind feature flags and set up Datadog monitors and product analytics.

• Leverage Cleric.ai to troubleshoot production issues and confirm features for users.

• Engage in the support rotation and manage incidents as they arise.

• Transform recurring support challenges into new briefs.

• Share expertise, patterns, and insights with the shared context repository.

• Within the first 90 days: establish an AI-native environment, deliver a scoped project with a pod, participate in a support rotation, and contribute a skill or learning to the shared repository.

⛳️ Requirements

• Over 6 years of experience in developing and managing production software.

• Extensive backend expertise with the capability to work across the technology stack.

• Familiarity with an AI-native setup utilizing tools such as Claude Code, Codex, Cursor, or similar technologies.

• Proficient in managing skills, rules, MCP servers, or agent workflows, with proven experience running agents in parallel.

• Strong analytical skills to assess agent outputs, including detecting bugs, security vulnerabilities, and architectural deviations.

• Experience in designing distributed systems on AWS, including event-driven architectures, queues, idempotency, failure recovery, and cost management.

• Accountability for ensuring quality in the absence of a QA team, incorporating test strategies, CI, observability, feature flags, and incident response protocols.

• Demonstrated product sense with the ability to articulate customer value, streamline scope, and evaluate results.

• Proficient written communication skills in English.

• Adaptability to ambiguity and change.

• If located in Europe, the ability to work within the Brazil/Argentina time zone.

• Nice to have: experience in developing LLM-powered product features, internal agent tools, Gmail/Google Workspace/CRM integrations, or SOC 2/security-conscious SaaS engineering.

🏝️ Benefits

• Freedom to determine the building process, select tools, and decide when to release behind a feature flag.

• Immediate impact with no layers separating engineering from product, design, customer success, or leadership.

• Chance to influence the company's AI-native operational model.

• Flexible remote work options.