Golang Engineer

Remote from: Brazil
Annual salary: Undisclosed
Salary information is not provided for this position. Check our Salary Directory to estimate the average compensation for similar roles.
Department: Software Engineering
Employment type: Full Time,
Job posted: 18 May 2026
Apply before: 18 Jun 2026
Experience level: Senior
Views / Applies: 12 / 4

Transforming ideas into digital solutions with cutting-edge technology.

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AI Summary

This Senior Golang Engineer role involves developing high-performance backend services with event-driven architectures and Kafka. The position requires 5+ years of Go experience, distributed systems knowledge, and proficiency with AI-assisted development tools. You will design resilient microservices, APIs, and event pipelines while collaborating with cross-functional teams. The role is remote for candidates based in Brazil, operating under a B2B contract model.

Job Complexity

Easy Hard

AI Insight The role demands advanced Golang expertise, hands-on Kafka experience, and distributed systems knowledge, plus familiarity with AI tools, making it highly specialized and challenging.

Salary Analysis

AI Insight The salary was not specified in the listing. Based on US market data for Senior Golang Engineers, the median salary is approximately $155,000 per year. The range typically spans $120,000 to $200,000 depending on experience and location. Since the role is for Brazil-based candidates, local compensation may differ, but the B2B model suggests competitive rates.

Key Skills

Golang Apache Kafka Distributed Systems Microservices Event-Driven Architecture REST API gRPC Docker CI/CD AI-Assisted Development

Cover Letter Sample

I am writing to express my strong interest in the Senior Golang Engineer position. With over 5 years of advanced Golang experience and deep expertise in Kafka and event-driven architectures, I am confident in my ability to contribute to your team's success.

My background includes designing high-performance microservices, implementing resilient distributed systems, and leveraging AI-powered tools like GitHub Copilot to enhance productivity and code quality. I have extensive experience with cloud platforms, CI/CD pipelines, and automated testing.

I am particularly excited about the opportunity to work with a highly technical team and contribute to AI-driven engineering practices. My ability to collaborate across DevOps, Data Engineering, and AI teams ensures seamless integration and delivery.

As a Brazil-based professional, I am fully prepared for the B2B model and remote collaboration. I look forward to discussing how my skills align with your needs.

Possible Interview Questions

How have you used Kafka in a production environment to handle event-driven architectures? Can you describe a specific challenge with partitioning or consumer groups?

In my previous role, I designed a Kafka-based event pipeline for real-time analytics. One challenge was ensuring balanced partition consumption with varying message loads. I implemented custom partitioners and adjusted consumer group configurations to optimize throughput and avoid lag.

Explain how you would design a resilient microservice in Go that handles backpressure from a downstream service.

I would use Go's context package to set deadlines and propagate cancellation. The service would implement a buffered channel with a configurable size, and when the channel is full, incoming requests would be rejected with a 503 status. Additionally, I would use circuit breakers and retry with exponential backoff.

Describe your experience with AI-assisted development tools. How have they improved your engineering workflow?

I regularly use GitHub Copilot for code suggestions and test generation. It speeds up boilerplate code and helps discover idiomatic patterns. For debugging, I use ChatGPT to analyze error logs and propose fixes. Overall, these tools reduce development time by about 20% while maintaining quality.

How would you handle event versioning and schema evolution in a Kafka-based system?

I would use Avro schemas with Schema Registry to enforce compatibility. For backward-compatible changes, I add new fields with defaults. For breaking changes, I create a new topic and migrate consumers gradually. I also use envelope patterns with version metadata to handle multiple versions simultaneously.

Can you walk us through how you would profile and optimize a Go service that is experiencing high latency?

First, I would use pprof to profile CPU and memory usage, and identify hot paths. Then, I would analyze goroutine traces for blocking calls. Common fixes include optimizing database queries, adding caching, reducing lock contention, and tuning garbage collection. I also use benchmarking to validate improvements.

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.

Requirements

Advanced proficiency in Golang (5+ years), with deep understanding of concurrency, memory management, profiling, benchmarking, and idiomatic Go patterns.

Expert-level hands-on experience with Kafka.
Solid foundation in distributed systems principles: consistency, replication, fault tolerance, event-driven architecture, resiliency patterns, and backpressure handling.
Strong experience with microservices at scale, API design (REST/gRPC), and service-to-service communication.
Proficiency with Docker, CI/CD workflows, and automated testing (unit, integration, load).
Experience deploying and operating systems in modern cloud platforms (AWS/GCP/Azure), including monitoring, alerting, and autoscaling.
Practical experience using AI-powered development tools and modern AI-assisted engineering workflows in professional environments.
Strong understanding of software engineering fundamentals while effectively leveraging AI-enhanced development practices.
Experience integrating APIs, automation workflows, or AI-powered services into distributed architectures is considered a plus.
Strong communication skills and proficiency in English.
All candidates must be based in Brazil
Open to work in a B2B model

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