Golang Engineer
Role summary by JobGrid
Golang Engineer at Plain Concepts: Remote, Brazil; Full time; IT; Back End Engineer. This listing is part of JobGrid's Software engineer jobs from public company career pages. JobGrid adds normalized role facts, source context, and a path to the employer application page so candidates can compare the listing before applying.
- Location and workplace: Remote, Brazil
- Role classification: IT, Back End Engineer, Full time
- Source freshness: checked by JobGrid on 2026-06-08.
- Application path: candidates continue to the employer application page with non-personal referral tags.
We are seeking a Senior Golang Engineer with strong expertise in event-driven architectures, distributed systems, and modern AI-assisted software engineering practices. The ideal candidate has deep hands-on experience with Apache Kafka, high-performance backend engineering, and the ability to design resilient microservices at scale, while leveraging modern AI-powered development tools to improve productivity, code quality, and engineering efficiency.
You will join a highly technical engineering team working with modern practices such as microservices, observability, CI/CD, clean architecture, cloud-native development, and AI-assisted coding workflows.
Responsibilities
- Develop, maintain, and optimize high-performance backend services in Go (Golang).
- Build and improve event pipelines and messaging systems using Kafka (producers, consumers, partitions, consumer groups).
- Design APIs (REST/gRPC) and integrations across multiple backend microservices.
- Implement unit, integration, and performance tests.
- Collaborate closely with DevOps, Data Engineering, QA, and AI-focused teams.
- Contribute to architectural decisions regarding schemas, event versioning, idempotency, streaming patterns, and backpressure handling.
- Leverage AI-assisted development tools (e.g., GitHub Copilot, Cursor, ChatGPT, Claude, or similar) to improve development productivity, debugging, testing, documentation, and code quality.
- Contribute to the adoption of AI-driven engineering practices and developer productivity initiatives across the software development lifecycle.
- Design backend services and integrations capable of supporting AI/LLM-powered systems, intelligent automation workflows, and scalable data processing solutions.
- Evaluate and implement emerging AI engineering tools and frameworks to improve software delivery efficiency and engineering standards.