Senior AI Platform DevOps Engineer

Visa Hunt

United States

On-site

USD 150,000 - 206,000

Full time

14 days+

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Job summary

D-Wave Quantum Inc. is seeking an experienced AI Platform DevOps Engineer to design, build, deploy, and operate AI-powered tools, platforms, and workflows that boost developer productivity and accelerate quantum computing tech delivery.

You will collaborate with DevOps and Product Development teams to evolve our internal AI platform, integrating Bedrock, AI agents, n8n, ArgoCD, Artifactory, and related services into scalable, secure development workflows.

Qualifications

Bachelor’s degree in Computer Science, Computer Engineering, or 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, embeddings, vector search, reranking, context management, structured outputs, tool use, evaluation, and AI security practices.
Experience with AWS generative AI technologies, including Amazon Bedrock and AgentCore, 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 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 Python, Go, Groovy, or similar.
Experience integrating monitoring and observability solutions using 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.

Responsibilities

Design, implement, and operate our internal AI tools platform.
Work with our development teams to streamline our internal AI build processes and release management via continuous integration and deployment pipelines.
Build and operate deployment 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.
Continuously monitor and improve the performance, durability, and reliability of our internal AI platform.
Promote AI best practices across development teams in-compliance with 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.