Python Development Specialist, GenAI

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Create robust, reusable, and high-performance backend services utilizing Python.

• Design and enhance microservices architectures prioritizing modularity and scalability.

• Develop RESTful APIs incorporating versioning, authentication, and security measures.

• Maintain quality and performance through sophisticated testing methodologies and optimizations.

• Automate processes for build, testing, and internal library releases.

• Engage in code reviews, establish standards, and advocate for best practices.

• Examine incidents and suggest structural enhancements in production environments.

• Seamlessly integrate legacy and external systems adhering to interoperability best practices.

• Collaborate with architecture, product, QA, and operations teams to deliver business-aligned technical solutions.

⛳️ Requirements

• Expertise in Python with frameworks such as Django, Flask, or FastAPI.

• Experience in end-to-end backend development within a microservices framework.

• Proficient in version control (Git), build automation, and dependency management tools (pipenv, poetry).

• Knowledge of relational databases (PostgreSQL, MySQL) and familiarity with Redis.

• Skilled in REST API design and versioning using Swagger/OpenAPI.

• Experience with automated testing frameworks (pytest, unittest) and test-driven development (TDD).

• Understanding of SOLID principles, dependency injection, modularity, and design patterns (Factory, Strategy, etc.).

• Familiarity with cloud-agnostic architecture and container technologies (Docker, Kubernetes).

• Knowledge of CI/CD practices and semantic versioning.

• Expertise in performance optimization for Python applications.

• Awareness of NoSQL databases, Elasticsearch, and search engines.

• Understanding of Clean Architecture, Domain-Driven Design (DDD), Hexagonal architecture, and 12-Factor App methodology.

• Proficient in automation scripting (Bash/Shell) and packaging internal libraries.

• Experience with monitoring and observability tools (Grafana, CloudWatch, Splunk).

• Background in multi-cloud environments with a focus on cost optimization.

• Understanding of software security principles (OWASP, OAuth 2.0, JWT) and technical governance.

• Familiarity with the use of AI for productivity enhancements (e.g., GitHub Copilot).

🏝️ Benefits

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