Software Developer IV, Golang, Kubernetes

🕒 Agosto 3

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Rackspace Technology

SiteLinkedInTodas as Vagas

5001 - 10000 funcionários

Fundada em 1998

💼 Consultoria

📦 Logística

🤖 Inteligência Artificial

Consulting • Logistics • Artificial Intelligence

A Rackspace Technology é um provedor global de serviços gerenciados em nuvem que projeta, constrói, migra e opera ambientes multicloud, híbridos e de nuvem privada para empresas. Oferece consultoria, serviços profissionais e gerenciados em infraestrutura de nuvem, modernização de aplicativos, plataformas de dados, IA/ML (Foundry de IA/FAIR) e cibersegurança, além de hospedagem gerenciada, colocation e integrações de plataforma com os principais hyperscalers. A Rackspace atende indústrias reguladas e críticas, com foco em segurança, conformidade, otimização de custos e confiabilidade operacional.

Descrição

• Architect and build the RackAI platform • Design and develop highly scalable backend services in Go (Golang) • Build Kubernetes-native applications — operators, controllers, and platform services — using controller-runtime and kubebuilder. • Define and evolve the RackAI platform architecture for growth, reliability, security, and operational excellence. • Develop the APIs, automation frameworks, and platform capabilities that power AI-enabled products. • Champion cloud-native best practices: observability, resiliency, and operational readiness. • Lead an AI-first engineering culture • Coach engineers to get real leverage from AI tooling, and continually assess what to adopt next.

🎯 Requisitos

• Nine or more years in software development • Expert-level Go (Golang) development • Deep Kubernetes expertise — architecture, operations, and application development • Proven experience with distributed systems and microservices architectures • Strong command of RESTful APIs, event-driven systems, and service-oriented architecture • Solid grounding in software design patterns, CI/CD, DevOps, Git-based workflows, and secure coding practices. • Hands-on experience with AI coding assistants such as Claude Code , Kiro , Codex , and GitHub Copilot • Practical understanding of modern Generative AI and Large Language Models (LLMs) • Understanding of AI inference concepts, including model serving, latency, throughput, batching, performance improvements, optimizations, benchmarking of model inference. • Knowledge of model fine-tuning techniques, including supervised fine-tuning (SFT), LoRA, and parameter-efficient fine-tuning (PEFT).

🏖️ Benefícios

• Health insurance • Flexible work arrangements • Professional development opportunities