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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Developer IV (Golang & Kubernetes) - **Company:** Rackspace - **Location:** San Antonio, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Cloud Engineering, Software Quality, Continuous Integration, Software Design Patterns, DevOps, Distributed Systems, Open Source Technology, Reliability Engineering, Prometheus, Azure Machine Learning, Search Technologies, Secure Coding, Service-Oriented Architecture, Software Engineering, Private Cloud Environment, Google Cloud, Spring Cloud, GitHub Copilot, Istio, System Availability, Large Language Models, Grafana, Prompt Engineering, Generative AI, Event Driven Architecture, Containerization, AI Platforms, Git Flow, Kubernetes, Low Latency, Deployment Automation, Machine Learning Operations, TensorRT, Hardware Infrastructure, Restful APIs, Oracle Cloud Infrastructure, Docker, Golang, Microservices - **Published:** September 18, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/pl4rspwj3b ## About the Role * 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. * Hands-on with container technologies such as Docker and OCI-compliant runtimes. * Solid grounding in software design patterns, CI/CD, DevOps, Git-based workflows, and secure coding practices. Experience * Nine or more years in software development, including five or more years writing production Go. * Demonstrable experience building Kubernetes operators or controllers with controller-runtime or kubebuilder. * A track record of delivering production-grade cloud-native applications. * Experience leading complex technical projects end to end, and mentoring engineers to a higher standard. AI-assisted development * Hands-on experience with AI coding assistants such as Claude Code, Kiro, Codex, and GitHub Copilot, integrated effectively into day-to-day engineering. * A genuine commitment to working within - and helping to shape - an AI-first development culture. AI and machine learning * Practical understanding of modern Generative AI and Large Language Models (LLMs). * Familiarity with open-source foundation models such as Llama, Mistral, Gemma, Qwen, or DeepSeek. * 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). * Understanding of Retrieval-Augmented Generation (RAG), vector databases, embeddings, and semantic search. * Experience integrating AI models into production applications using APIs or self-hosted inference platforms. AI platform and infrastructure * Experience with containerised AI workloads on Docker and Kubernetes. * Familiarity with AI serving frameworks such as vLLM, Triton Inference Server, TensorRT-LLM, or similar technologies. * Understanding of GPU-accelerated computing and how AI workloads are deployed on modern GPU infrastructure. * Experience deploying scalable AI applications in cloud or private cloud environments. Nice to have * Experience building AI/ML platforms or AI-enabled enterprise products. * Advanced work with CRDs and operator patterns. * Cloud platforms - AWS preferred; Azure or Google Cloud also welcome. * Service mesh technologies and platform-engineering concepts. * Observability stacks such as OpenTelemetry, Prometheus, Grafana, or similar. * Contributions to open-source projects. ## Description * 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 * Make AI-assisted engineering the default way of working - champion an AI-driven, AI-first approach across the team. * Embed AI development tooling - Claude Code, Kiro, Codex, or GitHub Copilot - across the lifecycle, from design and coding through testing, review, and documentation. * Set the standards and guardrails for responsible, effective use of AI coding assistants - code quality, security, licensing, and human-in-the-loop review. * Turn AI augmentation into measurable gains in velocity and quality through prompt engineering and agentic workflows. * Coach engineers to get real leverage from AI tooling, and continually assess what to adopt next. Engineer the platform and infrastructure * Design and optimise Kubernetes deployments across multiple environments. * Automate provisioning, deployment, scaling, and lifecycle management. * Partner with Platform Engineering to raise developer productivity and platform reliability. * Ensure solutions meet security, compliance, and operational requirements. Lead and mentor * Provide technical leadership across multiple engineering teams. * Lead architectural reviews and design discussions, and set coding standards and patterns. * Mentor Software Developers I-III and grow engineering capability across the group. * Evaluate emerging technologies and recommend strategic investments. Collaborate across the organisation * Work closely with Product, Architecture, Data Science, SRE, and Security. * Translate business needs into scalable technical solutions. * Communicate architectural decisions and technical strategy to stakeholders. * Contribute to roadmap planning and long-term platform evolution. ## Related Videos - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Rate-limiting using eBPF and Istio: How to protect your SaaS customers from themselves](https://www.wearedevelopers.com/videos/100220-rate-limiting-using-ebpf-and-istio-how-to-protect-your-saas-customers-from-themselves) - [Go with the Flow: Stop the Leaks Before Your Memory's a Waterfall!](https://www.wearedevelopers.com/videos/100073-go-with-the-flow-stop-the-leaks-before-your-memory-s-a-waterfall) - [MLOps and AI Driven Development](https://www.wearedevelopers.com/videos/347-mlops-and-ai-driven-development) - [Supercharge your cloud-native applications with Generative AI](https://www.wearedevelopers.com/videos/950-supercharge-your-cloud-native-applications-with-generative-ai) ## Related Articles - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Got AI ideas but no money? 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