Sr. Production Engineer, Solutions Engineering

Job Description

Responsibilities

• Design and build AI agents that augment production reliability work – Develop agents that assist engineers with service health analysis, reliability recommendations, migration playbook generation, and risk identification, enabling faster decision-making while keeping humans in the loop for critical judgment calls
• Drive large-scale infrastructure modernization with AI-accelerated execution – Lead Kubernetes adoption and platform transitions using AI to generate automation, accelerate delivery, and create patterns that enable self-service adoption for standard use cases while tackling novel architecture challenges
• Transform consulting patterns into scalable platforms – Execute scoped reliability engagements with engineering teams, then encode successful approaches into AI-assisted tools, automation, and self-serve documentation that enable teams to handle similar problems independently while escalating complex challenges to experts
• Build the knowledge infrastructure that powers operational agent ecosystem – Create migration playbooks, operational runbooks, incident patterns, and best practices that democratize reliability expertise and raise the baseline capabilities of all engineers
• Develop software solutions to enable reliability and operability of large-scale distributed systems – Build a deep understanding of how systems behave, scale, interact and fail, and use that insight to identify risks and opportunities for remediation through automation
• Build tools and automation to eliminate toil and reduce operational overhead – Create frameworks, processes and best practices that encode reliability expertise into software, making operational excellence accessible to all engineers while freeing experts to tackle harder problems
• Build meaningful, insightful and actionable SLIs – Develop service level indicators that provide clear signals of system health and enable data-driven reliability decisions across Engineering
• Automate critical portions of engineering processes – Build automation that minimizes risk and maximizes the speed of innovation, enabling safe, rapid deployment and operational changes at scale
• Manage capacity and performance to help scale our infrastructure – Partner with teams to plan and optimize capacity across public and private clouds around the world, ensuring efficient resource utilization as grows

What we’re looking for:

• 5+ years of industry experience building and operating large-scale, high-performance distributed systems
• Bachelor’s degree in Computer Science or related field, or equivalent experience
• Strong programming skills in Python or Go – ability to build production-grade platforms, agents, and automation
• Deep knowledge of Linux/Unix internals and experience with open source infrastructure (MySQL, Kafka, Envoy, Hadoop, etc.)
• Infrastructure as Code experience (Terraform, Puppet, Chef, Ansible, Docker, Kubernetes)
• Experience deploying web applications to cloud infrastructure (AWS, GCP, or Azure) and working with distributed, service-oriented architecture
• Preferred:
  • Experience developing AI agents for infrastructure automation, operational decision-making, or reliability workflows
  • AI/ML infrastructure experience (LLM-based systems, model serving, agentic workflows)
  • Technical consulting or embedded SRE experience with cross-functional engineering teams

Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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