Senior AI DevOps Developer in Abbeyville, Colorado at Jobgether
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Job Description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior AI DevOps Developer based in United States .
This is a senior technical opportunity focused on building and operating AI-powered platforms that improve developer productivity and accelerate software delivery. You will design scalable AI infrastructure, automate development workflows, and help engineering teams adopt reliable and secure AI capabilities. The role sits at the intersection of DevOps, cloud infrastructure, generative AI, automation, and platform engineering. You’ll work with technologies such as Amazon Bedrock, AI agents, Kubernetes, Terraform, ArgoCD, and modern observability platforms. You will also influence AI platform architecture, security practices, deployment strategies, and operational standards across development teams. The position offers the opportunity to solve complex technical challenges while helping shape how AI is integrated into modern engineering environments.
- Design, implement, deploy, and operate an internal AI tools and platform ecosystem that supports engineering productivity and innovation.
- Build and improve CI/CD pipelines for AI-enabled development workflows, including model, prompt, and evaluation deployment processes.
- Develop robust versioning, cost-tracking, monitoring, testing, and rollback strategies for AI models, prompts, and related services.
- Integrate AI technologies and services such as Amazon Bedrock, AI agents, workflow automation platforms, and supporting infrastructure into secure and scalable development environments.
- Apply DevOps and platform engineering best practices to improve the performance, durability, availability, and reliability of AI services.
- Design and maintain infrastructure-as-code, containerized deployments, artifact management, and continuous delivery environments.
- Participate in security reviews and compliance initiatives, implementing appropriate access controls, service configurations, data-handling practices, and security safeguards.
- Develop and maintain AI-powered development, on-call, and agentic workflows that automate repetitive tasks and reduce operational overhead.
- Integrate monitoring and observability solutions to provide visibility into system health, performance, usage, and reliability.
- Troubleshoot operational incidents, respond to platform-related questions, and conduct root-cause analysis to prevent recurring issues.
- Partner with engineering teams to identify AI opportunities, translate business and development workflows into technical solutions, and continuously improve platform capabilities.
- Establish and promote AI usage policies, guardrails, data-handling standards, and responsible AI practices across development teams.
- Lead AI platform architecture discussions, evaluating model, infrastructure, tooling, and design trade-offs.
- Facilitate AI office hours and technical discussions to share knowledge and encourage effective adoption of AI capabilities.
- Participate in an on-call rotation to help maintain the high availability and reliability of critical applications and platform services.
- Bachelor’s degree in Computer Science, Computer Engineering, or a related technical discipline, or equivalent professional experience.
- 5+ years of experience designing, deploying, operating, and troubleshooting modern cloud-based or on-premises infrastructure, DevOps platforms, or SaaS/PaaS environments.
- Hands-on experience building and supporting production AI applications, including LLM applications, AI agents, generative AI solutions, or workflow automation.
- Strong understanding of the modern LLM application stack, including prompt engineering, RAG, embeddings, vector search, reranking, context management, structured outputs, tool use, evaluations, and AI security.
- Experience with AWS generative AI technologies, particularly Amazon Bedrock and AgentCore.
- Familiarity with agentic orchestration frameworks and interoperability protocols such as MCP and ACP.
- Strong experience designing and operating CI/CD pipelines, infrastructure-as-code, artifact management, and containerized deployment environments.
- Hands-on knowledge of technologies such as Kubernetes, Terraform, ArgoCD, Artifactory, Jenkins, and Git, or equivalent platforms.
- Strong Linux administration and troubleshooting capabilities, including log analysis, system diagnostics, SSH, certificates, security fundamentals, and automation.
- Programming or scripting experience with Python, Go, Groovy, or comparable languages.
- Experience integrating monitoring and observability solutions such as Grafana, OpenSearch, Prometheus, InfluxDB, Zabbix, or equivalent tools.
- Experience integrating third-party services and REST-based APIs within Linux-based environments.
- Strong problem-solving skills and the ability to independently investigate and resolve ambiguous technical challenges.
- Ability to collaborate effectively across engineering teams and translate business or development workflows into scalable technical solutions.
- Strong communication skills and the ability to influence technical decisions, facilitate discussions, and share knowledge with diverse engineering audiences.
- A proactive, accountable, and innovative mindset, with a willingness to challenge established approaches and explore new possibilities.
- Competitive annual base salary of $150,000–$206,000 CAD for candidates based in Canada.
- Opportunity to participate in a broader total rewards package, potentially including equity, bonus opportunities, and additional perks.
- Remote work opportunity within Canada.
- Work on cutting-edge AI, cloud, DevOps, and platform engineering initiatives.
- Opportunity to work with emerging technologies including generative AI, AI agents, Amazon Bedrock, Kubernetes, infrastructure-as-code, and agentic workflows.
- Exposure to complex engineering challenges within an innovative research and development environment.
- Opportunity to influence AI platform architecture, engineering standards, security practices, and responsible AI adoption.
- Collaborative culture that values diverse perspectives, open communication, accountability, learning, and professional growth.
- Opportunities to expand technical leadership through architecture discussions, team enablement, AI office hours, and cross-functional initiatives.
- Meaningful opportunity to contribute to the development of technologies shaping the future of computing.