Staff Software Engineer, Product

Jobgether; Brazil; Remote; BRL 474,000 - 697,000; Full time

Benefits offered by this job

Fully Remote Work

Job summary

Jobgether is seeking a Staff Software Engineer, Product, based in Brazil, to lead AI‑driven, end‑to‑end product engineering initiatives in a fast‑growing marketplace. You will own architecture, data models, and deployment strategies, guiding AI agents to deliver high‑quality software across web and mobile platforms.

You will collaborate with PMs and designers to translate business needs into practical tech solutions, drive measurable outcomes, and raise engineering productivity through AI

Qualifications

• Extensive software engineering experience with a track record of leading complex initiatives.
• Experience at senior technical leadership or staff engineer level is essential.
• Strong practical experience using AI coding agents as part of daily development.
• Ability to direct AI agents through prompts, loops, and evaluation workflows.
• Proven capability to make independent architectural decisions and own technical direction.
• Understanding of translating business needs into technical solutions with measurable impact.
• Experience evaluating post-launch performance and business outcomes.
• Deep production experience in at least one AI-enabled stack.

Responsibilities

• Lead end-to-end product engineering initiatives from discovery to production.
• Own architecture, data models, integrations, and rollout strategies.
• Guide AI coding agents to accelerate implementation while ensuring quality.
• Maintain robust testing, code reviews, and production readiness.
• Collaborate with PMs and designers on scope and UX decisions.
• Coordinate across teams to maintain consistency and knowledge sharing.
• Focus on measurable business outcomes like conversion and retention.
• Ensure production excellence in security, observability, and performance.
• Develop and improve AI agent workflows and documentation.
• Document architectural decisions and runbooks for long-term maintenance.

Skills

AI-native development

Staff engineer level

Technical leadership

Product engineering mindset

Tools

PHP

Laravel

TypeScript

React

React Native

AWS

Datadog

Sentry

GitHub Actions

Confluence

Jira

Job description

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Staff Software Engineer, Product based in Brazil.

We are looking for an experienced, AI-native Staff Software Engineer to lead end-to-end product engineering initiatives in a fast-paced, high-growth marketplace environment. In this role, you will combine strong technical expertise, product thinking, and AI-powered development practices to deliver impactful solutions from initial concept to production. Working closely with Product Managers, designers, and engineering peers, you will own technical decisions, guide AI coding agents, and ensure the delivery of reliable, high-quality software. You will have significant autonomy in shaping architecture, implementation strategies, and deployment approaches while remaining accountable for measurable business outcomes. Your work will directly influence customer and service professional experiences across web and mobile platforms. This is an opportunity to operate at staff-level responsibility, accelerate engineering productivity through AI innovation, and make a tangible impact in a real-world marketplace.

Accountabilities

• End-to-End Product Engineering: Lead engineering initiatives from problem definition and technical discovery through architecture, implementation, production deployment, and post-launch performance evaluation.
• Technical Architecture and Decision-Making: Own the technical approach for assigned initiatives, including system architecture, data models, integrations, rollout strategies, observability, and rollback plans. Make independent technical decisions while involving architects in significant architectural choices.
• AI-Driven Software Development: Leverage AI coding agents such as Claude Code, Cursor, Codex, and equivalent tools to accelerate implementation. Design effective prompts, agent workflows, and guardrails to ensure AI-generated code meets production engineering standards.
• Implementation Quality and Reliability: Establish and maintain robust testing strategies, evaluations, code review processes, and validation mechanisms to ensure AI-assisted implementations are secure, reliable, scalable, and production-ready.
• Cross-Functional Collaboration: Work closely with Product Managers to define scope, prioritize requirements, and evaluate trade-offs, while partnering with designers on user experience decisions and prototyping.
• Shared Codebase Collaboration: Coordinate with engineering peers across multiple initiatives, maintaining consistency, sharing technical knowledge, and contributing to the overall quality of the engineering organization.
• Business and Product Outcomes: Take ownership of the success metrics associated with each initiative, such as conversion rates, customer retention, service professional funnel performance, and unit economics.
• Performance Measurement: Collaborate with Product Managers to review initiative results approximately 2–4 weeks after launch, analyze performance data, and identify whether the intended business outcomes were achieved.
• Production Excellence: Maintain high standards for software correctness, security, performance, observability, and user experience across all customer- and professional-facing products.
• Deployment and Risk Management: Implement appropriate testing, staged rollouts, monitoring, and review gates to minimize regressions and ensure safe production releases.
• AI Workflow Innovation: Continuously improve AI agent workflows, prompts, evaluation frameworks, and review processes, sharing reusable practices that increase productivity across engineering teams.
• Technical Documentation: Document architectural decisions, implementation approaches, operational runbooks, agent workflows, and post-launch findings to support knowledge sharing and long-term maintainability.
• Continuous Improvement: Identify opportunities to reduce development cycle times, improve engineering efficiency, and strengthen the relationship between technical delivery and measurable product impact.

Requirements

• Professional Experience: Extensive professional experience in software engineering, with a proven track record of leading complex technical initiatives and delivering production-ready product solutions. Experience operating at a senior technical leadership or Staff Engineer level is essential.
• AI-Native Development: Strong practical experience using AI coding agents such as Claude Code, Cursor, Codex, or equivalent tools as part of daily production development. Ability to direct AI agents through effective prompting, agent loops, evaluation frameworks, and review workflows.
• AI-Assisted Engineering Quality: Experience building development workflows in which AI agents perform substantial implementation work while you remain responsible for technical direction, code quality, testing, and production readiness.
• Technical Leadership: Demonstrated ability to make independent architectural and engineering decisions, solve complex technical problems, manage trade-offs, and take accountability for the success of delivered solutions.
• Product Engineering Mindset: Strong understanding of product development principles, with the ability to translate business needs and customer problems into practical technical solutions that deliver measurable results.
• Outcome Orientation: Experience defining, tracking, and improving product or business metrics. Ability to evaluate post-launch performance, interpret data, and make informed decisions based on measurable outcomes rather than development output alone.
• Technical Stack: Deep expertise in at least one relevant technology stack, with credible production experience in AI-assisted development. The environment includes:
  • AI and Development Tools: Claude Code, Cursor, Codex, internal AI agent platforms, MCP servers, and evaluation tooling.
  • Backend: PHP and Laravel.
  • Frontend and Mobile: TypeScript, React, and React Native, supporting web and mobile applications.
  • Data and Analytics: Amazon Redshift, dbt, Segment, and Airflow.
  • Cloud and Infrastructure: AWS, Datadog, Sentry, and GitHub Actions.
  • Documentation and Collaboration: Confluence, Jira, and internal knowledge systems supporting AI agent workflows and technical documentation.
• Software Architecture and Engineering Practices: Strong understanding of system design, data modeling, API integrations, testing strategies, deployment processes, observability, and production reliability.
• Cross-Functional Partnership: Ability to work effectively with Product Managers, designers, architects, and engineering peers, contributing technical judgment to product decisions and product perspective to engineering discussions.
• Autonomy and Accountability: Comfortable working independently, making decisions quickly, documenting technical choices, seeking feedback when appropriate, and taking responsibility for the results.
• Communication and Knowledge Sharing: Strong communication skills and the ability to explain complex technical concepts, mentor peers, and create reusable documentation, workflows, and engineering practices.
• Customer Focus: Genuine interest in building products that improve experiences for both customers and service professionals within a two-sided marketplace.
• Continuous Learning: Curiosity and adaptability, with a strong interest in emerging AI technologies, modern software engineering practices, and continuous product improvement.
• Leadership Development: This is primarily an individual contributor position, with people management responsibilities currently handled by Engineering Managers. Previous management experience is not required, although opportunities to transition into people leadership may become available.

Benefits

• Competitive Compensation: Annual base salary ranging from USD $85,000 to $125,000, depending on experience and qualifications.
• Fully Remote Work: Work from anywhere, offering flexibility and location independence.
• High Ownership and Autonomy: Significant responsibility for technical decisions, product initiatives, and measurable business outcomes.
• AI-Driven Engineering Environment: Opportunities to work with advanced AI coding agents and innovative development workflows.
• Professional Growth: Exposure to complex product challenges, modern technologies, and staff-level engineering responsibilities.
• Collaborative Culture: Join a fast-moving engineering team that values building, learning, experimentation, and continuous improvement.
• Career Development: Opportunities to expand technical leadership and potentially explore people management as the organization evolves.
• Real-World Product Impact: Contribute directly to products used by customers and service professionals within an established, high-volume marketplace.

How Jobgether Works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

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