Senior DevOps Engineer

Job Description

Senior DevOps Engineer

Compensation: $150,000 - $180,000 base + profit sharing

Location: Greater San Diego, CA, onsite 5 days per week

Join an established global enterprise technology company making significant investments in AI infrastructure, platform engineering, and modern developer tooling.

This is a senior-level opportunity for a hands-on DevOps Engineer who combines deep cloud infrastructure expertise with the ability to design, build, and maintain production-grade systems supporting AI applications and services.

The Mission

The company is building and scaling a centralized AI platform that enables engineering teams to develop, deploy, and operate production AI applications reliably. Rather than focusing on isolated proofs of concept, the team is developing infrastructure that supports real-world AI services, including retrieval-augmented generation (RAG), internal developer tools, and enterprise AI applications.

The Role

You will join a dedicated AI Engineering function responsible for the infrastructure and deployment practices supporting a growing portfolio of internal AI platforms. This is a hands-on engineering position combining traditional DevOps, cloud infrastructure, platform engineering, and emerging AI infrastructure requirements.

You will work extensively with AWS, Terraform, Kubernetes, CI/CD pipelines, and infrastructure automation while helping define the engineering standards that other teams will adopt.

The team is relatively small, meaning you will have significant ownership over technical decisions, infrastructure architecture, and the evolution of its production environment.

The company is looking for someone who can independently design and implement solutions rather than simply maintain infrastructure that others have already built.

What You'll Do

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• Design, build, and maintain production-grade AWS infrastructure supporting internal AI platforms and applications.
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• Develop and manage infrastructure as code using Terraform, ensuring environments are scalable, repeatable, and maintainable.
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• Build, deploy, and operate containerized applications using Kubernetes, including AWS-managed container orchestration services.
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• Design, implement, and optimize CI/CD pipelines using GitHub Actions and modern deployment automation practices.
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• Support infrastructure for production AI applications, including RAG-based systems and internal AI services.
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• Establish monitoring, logging, alerting, and observability practices to maintain production reliability and performance.
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• Improve infrastructure security, availability, scalability, and operational resilience.
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What You'll Bring

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• Strong hands-on experience in DevOps Engineering, Site Reliability Engineering, Cloud Infrastructure, or Platform Engineering.
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• Deep production experience with AWS, including infrastructure design, deployment, networking, security, and operational management.
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• Strong proficiency with Terraform and infrastructure-as-code practices.
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• Hands-on experience with Kubernetes and containerized application deployments, ideally within AWS environments such as EKS.
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• Experience building and maintaining CI/CD pipelines, particularly using GitHub Actions.
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• Strong automation and scripting capabilities, ideally with Python and Bash.
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• Experience designing, implementing, and owning infrastructure rather than exclusively supporting established environments.
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• Strong understanding of production reliability, observability, monitoring, troubleshooting, and incident response.
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About People In AI

We partner with AI-first startups, scale-ups, and enterprise organizations to connect exceptional engineers with opportunities to build production AI systems, intelligent platforms, and the next generation of AI infrastructure.