Staff Software Engineer, Product
New
J
JobgetherHome services marketplace
Based in BrazilFull-TimeStaff
Salary85,000 - 125,000 USD per year
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Job Details
- Experience
- Extensive software engineering experience operating at a staff or lead level
- Required Skills
- AWSPHPReact NativeSoftware ArchitectureTypeScriptReactData modelingDatadog
Requirements
- Bring extensive software engineering experience at staff or lead level, with a record of making important technical decisions and delivering complex initiatives.
- Have strong hands-on experience using AI coding agents in daily production development, such as Claude Code, Cursor, Codex, or equivalent tools.
- Direct AI agents through prompting, context management, evaluation, testing, and code-review workflows, while owning the resulting code.
- Have deep technical expertise in at least one relevant technology stack and experience delivering and maintaining production software.
- Have experience with one or more of: PHP and Laravel; TypeScript, React, or React Native; Redshift, dbt, Segment, or Airflow; AWS, Datadog, Sentry, or GitHub Actions.
- Understand software architecture, data modeling, system integrations, testing, deployment strategies, security, performance optimization, and production observability.
- Lead initiatives independently, make timely and documented technical decisions, and balance autonomy with collaboration and review.
- Translate business goals and customer needs into technical solutions and prioritize work based on measurable impact.
- Partner effectively with product managers, designers, and engineering colleagues in cross-functional teams.
- Interpret performance metrics, evaluate outcomes, and use data to guide decisions.
- Develop reusable engineering practices and documentation that improve productivity and technical quality.
- Be interested in an individual-contributor role with technical leadership responsibilities; people management is not required.
Responsibilities
- Lead technical direction for product initiatives, including architecture, data modeling, integrations, observability, deployment strategies, and rollback planning.
- Own the product development lifecycle from problem definition and technical planning through implementation, production release, and post-launch evaluation.
- Use AI coding agents to accelerate development, with prompts, guardrails, evaluation workflows, testing strategies, and review processes.
- Maintain security, performance, reliability, maintainability, and user experience standards.
- Make and document technical decisions, seeking peer input and architecture review when appropriate.
- Partner with product managers and designers to prioritize opportunities, define scope, assess trade-offs, and deliver customer-aligned solutions.
- Track initiative outcomes, including conversion, retention, service-provider engagement, and unit economics.
- Conduct post-launch reviews two to four weeks after release to evaluate results and lessons.
- Establish reusable AI development workflows, evaluation tools, runbooks, documentation, and best practices.
- Identify and address regressions through testing, monitoring, staged rollouts, and quality-control measures.
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