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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI DevOps Developer - **Company:** D-Wave Quantum Inc. - **Location:** Circle, AK, United States (Remote available) - **Experience:** Expert - **Salary:** $150,000.0 - $206,000.0 - **Contract:** Permanent contract - **Skills:** Secure Shell (SSH), Application Programming Interfaces (APIs), Artificial Intelligence, Software as a Service, Computer Engineering, Continuous Integration, DevOps, Groovy, Interoperability, Python (Programming Language), Linux System Administration, Log Analysis, Octopus Deploy, Platform as a Service (PAAS), Quantum Computing, Release Management, Prometheus, Search Technologies, Systems Integration, Management of Software Versions, Zabbix, Data Processing, System Availability, Delivery Pipeline, Large Language Models, Grafana, Prompt Engineering, Generative AI, Git, AI Platforms, Kubernetes, Information Technology, Influxdb, Build Process, Hardware Infrastructure, Terraform, Jenkins, Artifactory, Golang - **Published:** August 11, 2026 - **Apply:** https://www.workingnomads.com/job/go/1783436/ ## About the Role * Bachelor's degree in Computer Science, Computer Engineering, or a related technical discipline, or equivalent experience * 5+ years of experience designing, deploying,operating, and troubleshooting modern cloud-based and on-premises infrastructure, DevOps platforms, or SaaS/PaaS environments * Hands-on experience building and supporting production AI applications, including LLM applications, AI agents, workflow automation, or generative AI solutions * Strong understanding of the LLM application stack, including prompt engineering, retrieval-augmented generation (RAG), embeddings, vector search, reranking, context management, structured outputs, tool use, evaluation, and AI security practices * Experience with AWS generative AI technologies, including Amazon Bedrock andAgentCore, as well as agentic orchestration frameworks and interoperability protocols such as MCP and ACP * Experience designing and operating CI/CD pipelines, infrastructure-as-code, artifact management, and containerized deployment environments using technologies such as Kubernetes, Terraform,ArgoCD, Artifactory, Jenkins, Git, or equivalent tools * Strong Linux administration skills, including troubleshooting, log analysis, system diagnostics, SSH, certificates, security fundamentals, and automation using languages such as Python, Go, Groovy, or similar * Experience integrating monitoring and observability solutions using tools such as Grafana, OpenSearch, Prometheus,InfluxDB, Zabbix, or equivalent technologies * Experience integrating third-party services and APIs, including REST-based integrations, within Linux-based environments * Ability to work independently, solve ambiguous technical problems, collaborate across teams, and translate business workflows into scalable technical solutions ## Description D-Wave is seeking an experienced AI Platform DevOps Engineer to join our Product Development team. In this role, you will design, build, deploy, andoperateAI-powered tools, platforms, and workflows that improve developer productivity, automate repetitive tasks, reduce operational overhead, and accelerate the delivery of our quantum computing technologies. Working alongside talented DevOps engineers and Product Development teams, you will help build and evolve our internal AI platform, integrating technologies such as Amazon Bedrock, AI agents, n8n, Artifactory,ArgoCD, and other supporting services into scalable, secure, and reliable development workflows. You will play a key role in designing and operating AI-powered development, on-call, and agentic workflows, partnering across engineering teams to prioritize, implement, and continuously improve AI initiatives that enable innovation across the organization. What you'll do * Design, implement, andoperateour internal AI tools platform * Work with our development teams to streamline our internal AI build processes and release management(build processes and release management processes that incorporate AI (to function) and build processes and release management of AI-related tools, solutions, workflows)via continuous integration and deployment pipelines * Build andoperatedeployment pipelines for models, prompts, and evaluations, including versioning, cost tracking, and rollback strategies * Participate in security reviews and compliance efforts, designing and implementing the security controls, access rules, and service configurations needed to meet those requirements * Apply DevOps best practices to testing and monitoring, continuously improving the performance, durability, and reliability of our internal AI platform * Respond to operational incidents and development questions related to our internal AI platform and perform root-cause analysis * Continuouslymonitorand improve the performance, durability, and reliability of our internal AI platform * Promote AI best practices (usage policies, guardrails, and data handling standards) across development teams in-compliancewith company policy * Participate in AI office hours and lead group discussions * Lead AI platform architecture discussions relating to model and design tradeoffs * Join the on-call rotation to help ensure the high availability and reliability of D-Wave applications, * We look at the future and say "why not"; we see possibilities where others see problems or routines. We show the way ahead and are committed to achieving ambitious goals. * We practice straight talk and listen generously to each other with empathy. We value different opinions and points of views. We ensure that we connect outside as well as inside to learn from others and inspire each other. * We hold ourselves accountable for delivering results. We make decisions & take responsibility so that we can act & support each other. * As leaders we motivate & engage our teams to undertake beyond what they originally thought possible, by developing our teams & creating the conditions for people to grow and empower themselves through enabling & coaching. ## Related Videos - [DevOps for AI: running LLMs in production with Kubernetes and KubeFlow](https://www.wearedevelopers.com/videos/1222-devops-for-ai-running-llms-in-production-with-kubernetes-and-kubeflow) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [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) - [How to Avoid LLM Pitfalls - Mete Atamel and Guillaume Laforge](https://www.wearedevelopers.com/videos/1328-how-to-avoid-llm-pitfalls-mete-atamel-and-guillaume-laforge) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [Scoring 2000 Products per Request: Performance Pitfalls in Golang](https://www.wearedevelopers.com/videos/2073-scoring-2000-products-per-request-performance-pitfalls-in-golang) ## Related Articles - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [ Dev Digest 213: Petrol Prices, Agentic Workflows, AI Skills and CODE100!](https://www.wearedevelopers.com/magazine/718-dev-digest-213-petrol-prices-agentic-workflows-ai-skills-and-code100)