Senior Software Engineer - Backend Legal Pros

Accountabilities:: Design, develop, and maintain scalable backend services and applications using Python, Go, or similar technologies. Contribute to the evolution of search and evaluation systems, addressing complex challenges related to ranking, search relevance, experimentation, and user behavior. Build and optimize high-performance APIs and distributed systems capable of handling large volumes of data and traffic. Develop and maintain REST APIs and asynchronous communication mechanisms, including queues and event-driven architectures. Work with relational databases, ensuring efficient data storage, retrieval, consistency, and performance. Collaborate with engineering leadership and product teams to define technical solutions, contribute to architectural decisions, and deliver improvements to the search experience. Design, implement, and analyze experiments, including A/B tests, to evaluate system performance and continuously improve product behavior based on data. Monitor application performance, reliability, and scalability, identifying bottlenecks and implementing optimization strategies. Integrate AI-powered capabilities into backend systems and development workflows, leveraging automation, code generation, and AI agents to improve engineering productivity. Participate in technical discussions, code reviews, and knowledge-sharing initiatives, contributing to engineering excellence and continuous improvement. Take ownership of complex technical challenges, proactively identifying opportunities for innovation and delivering solutions with increasing autonomy. Requirements: Strong professional experience in backend software development using Python, Go, or similar programming languages. Familiarity with REST APIs and asynchronous communication patterns, including messaging queues and event-driven systems. Solid experience with relational databases, particularly PostgreSQL or similar technologies. Experience designing, developing, and maintaining distributed systems and high-scale applications. Strong analytical and problem-solving skills, with the ability to work with experimentation, testing, metrics, and data-driven optimization. Experience using data to evaluate system performance, identify improvement opportunities, and support technical decisions. Strong technical communication skills and the ability to collaborate effectively with engineering peers, product teams, and other stakeholders. Practical and consistent use of AI tools as part of everyday software development, including automation, code generation, and AI agents. Candidates should demonstrate fluent, hands-on usage rather than occasional experimentation. Adaptability and enthusiasm for continuous learning, particularly in environments involving emerging technologies and evolving technical challenges. Previous experience with search systems is not mandatory. Nice to have: Experience working with high-throughput systems, large-scale data processing, or messaging technologies such as Kafka and RabbitMQ. Familiarity with observability, application monitoring, system reliability, and Site Reliability Engineering (SRE) principles. Experience with Large Language Models (LLMs) or integrating AI models into software products. Knowledge of cloud infrastructure and services, particularly Google Cloud Platform (GCP) or AWS. Previous experience developing or maintaining search systems using Elasticsearch or similar technologies. Academic background, particularly a master's degree or PhD in a relevant field. Experience publishing research papers or contributing to applied research projects. Benefits: Fully remote work model, with the flexibility to work from anywhere in Brazil. Opportunity to work on highly complex, large-scale technology challenges with significant real-world impact. Collaborative environment with experienced engineering and product professionals. Exposure to cutting-edge technologies, including artificial intelligence, LLMs, distributed systems, and large-scale search infrastructure. Opportunities for continuous technical learning, experimentation, and professional development. Autonomy and ownership over meaningful technical initiatives. Opportunity to contribute to products that improve access to legal information and support the evolution of the justice system. Inclusive recruitment process, with accessibility accommodations available for candidates with disabilities.