Sr. Production Engineer, Solutions Engineering

Навыки

• Ansible
• AWS
• Azure
• Решения на данных
• Распределённые системы
• Docker
• Google Cloud

О компании и продукте

• Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.
• Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.
• At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.
• Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here .

Задачи

• 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 Pinterest's operational agent ecosystem - Create migration playbooks, operational runbooks, incident patterns, and best practices that democratize reliability expertise and raise the baseline capabilities of all Pinterest engineers
• Develop software solutions to enable reliability and operability of large-scale distributed systems - Build a deep understanding of how Pinterest's 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 Pinterest Engineering
• Automate critical portions of Pinterest's 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 Pinterest grows

Требования

• 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

Паспорт вакансии

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