Engenharia de Software Backend Sênior - Python | RD Station

Accountabilities: AI Product Development: Lead the ongoing evolution of an AI Agent Builder product, delivering high-quality backend capabilities aligned with user needs and product objectives. Backend Engineering: Design, develop, and maintain scalable, resilient, and observable backend services using Python, ensuring the platform can support continued growth. Technical Architecture: Lead solution design discussions and make sound architectural decisions consistent with engineering standards, system requirements, and broader technical strategy. Cross-Functional Delivery: Collaborate closely with Product, Design, and Frontend Engineering to translate business needs into sustainable technical solutions, anticipate dependencies, and remove delivery blockers. Technical Leadership and Mentoring: Serve as a technical reference for the engineering team, conduct code reviews, provide constructive feedback, and share knowledge to improve engineering practices. Service Reliability and Performance: Monitor service health, improve observability and performance, support incident management, and address technical debt to maintain platform stability. Roadmap and Delivery Management: Help ensure predictable delivery by balancing development speed, code quality, scalability, and long-term maintainability. AI-Assisted Development: Use AI-powered development tools, such as Cursor, to improve productivity while maintaining responsibility for code quality, security, and maintainability. Continuous Improvement: Encourage engineering excellence, contribute to technical discussions, and identify opportunities to improve development workflows, architecture, and team effectiveness. Requirements Python Backend Development: Strong professional experience building, maintaining, and evolving complex backend applications and services using Python. Software Architecture: Experience designing software architectures, REST APIs, distributed systems, and integrations between services. Engineering Best Practices: Strong understanding of SOLID principles, design patterns, automated testing, code quality, and maintainable software development. Databases and Asynchronous Processing: Experience with relational and/or NoSQL databases, along with asynchronous processing or event-driven architectures. Cloud and Delivery Infrastructure: Practical experience with cloud environments, CI/CD pipelines, and observability practices. Technical Leadership: Experience acting as a technical reference or informal/formal tech lead, guiding engineers through code reviews, architectural decisions, and technical discussions. Technical Decision-Making: Ability to evaluate trade-offs involving scalability, performance, security, delivery timelines, and business impact. Cross-Functional Collaboration: Ability to work effectively with multidisciplinary teams and provide technical direction across backend and frontend development. AI-Assisted Development Tools: Familiarity with AI-powered coding assistants and the ability to use them responsibly to improve engineering efficiency. Ownership and Communication: Strong sense of ownership, clear communication, pragmatic problem-solving, and curiosity to learn in a rapidly evolving technical environment. Generative AI Experience: Experience with generative AI products, large language models (LLMs), or AI agents is a strong advantage. Agent Architecture and Prompt Engineering: Familiarity with agent architectures, tool orchestration, and prompt engineering is desirable. Model Context Protocol (MCP): Experience with MCP and integrations between AI agents and external services is an advantage. LLMOps and AI Evaluation: Knowledge of LLMOps practices, AI application monitoring, and evaluation methodologies is desirable. Additional Technologies: Familiarity with React, TypeScript, Google Cloud Platform (GCP), Docker, Kafka, Pub/Sub, PostgreSQL, MongoDB, or Datadog is beneficial. Digital Product Experience: Experience working on rapidly evolving digital products with significant scalability challenges is a plus. Benefits Remote Work: Fully remote working arrangement within Brazil. Technical Ownership: Opportunity to influence architecture and lead the evolution of an AI-powered product. Professional Development: Opportunities to deepen expertise in Python, distributed systems, software architecture, and generative AI technologies. Technical Leadership Growth: Opportunity to mentor engineers, guide technical decisions, and strengthen leadership capabilities. Innovative Technology Environment: Work with AI-assisted development tools and modern engineering practices in a fast-evolving product environment. Collaborative Culture: Work closely with Product, Design, and Engineering teams to deliver solutions with meaningful business impact. Continuous Learning: Opportunities to explore emerging technologies, share knowledge, and contribute to engineering excellence. Well-Being and Inclusion: A workplace culture that emphasizes employee well-being, diversity, belonging, and the combination of human judgment with AI-enabled innovation. Compensation and Specific Benefits: Salary details, healthcare coverage, bonuses, and other specific benefits were not disclosed in the original job posting.