Systems Engineer

In 2024, Yext acquired Hearsay Systems, bringing together two industry leaders to form one unified organization. By combining Yext’s brand visibility expertise with Hearsay’s best-in-class compliant engagement solutions, we’re delivering even greater value to our customers. Our integrated approach unlocks a deeper set of data, insights, and recommendations — empowering brands to convert prospects into customers faster and more effectively. 

This is a hybrid position, offering the flexibility of remote telework with the requirement to be on-site at least one day per week on average. Occasional adjustments may be made based on team needs or project demands.

At Yext, our Systems Engineers craft the underlying infrastructure that powers the Yext platform that entails adapting the best open-source and commercial software into an infrastructure architecture that our software engineers can use to develop our products and services. We’re looking for systems engineers who are passionate about building and operating reliable, predictable, reproducible, transparent, and secure infrastructure platforms, while helping software engineers use them effectively.

We work in an agile environment with regular demos that keep teams aligned and give engineers clear visibility into the impact of their work. From day one, you’ll contribute directly to the codebase, learn from experienced engineers from a wide range of leading universities and technology companies, and build the skills needed to take on increasingly complex technical challenges.

What You’ll Do 

• Contribute to the building, maintaining, and improvement of infrastructure systems that power our core SaaS platform, with a focus on performance, security, reliability, and developer experience
• Collaborate effectively with Product Engineering, SRE, and Security teams to support infrastructure projects from planning through production
• Evaluate existing systems and contribute to improvements that increase scalability, resilience, and operational efficiency
• Build and manage infrastructure using infrastructure-as-code tools such as Terraform, Pulumi, or similar technologies
• Use configuration management tools such as Ansible, Chef, or similar to improve consistency and automation across environments
• Support containerized platforms and orchestration systems, including technologies such as Docker, Kubernetes, ECS, or Nomad
• Contribute to observability and operational excellence through monitoring, logging, alerting, and instrumentation improvements
• Document system designs, platform standards, and operational best practices, and help developers use them effectively
• Participate in an on-call rotation and help maintain the health, availability, and performance of production systems
• Participate in an on-call rotation, respond to production incidents, and contribute to follow-up efforts that improve the health, availability, and performance of production systems.
• Write clean, tested, and well-documented code
• Learn to diagnose technical problems, use engineering tools effectively, and ask thoughtful questions when additional input is needed
• Participate in code reviews and learn to evaluate technical approaches and implementation choices
• Use AI-assisted development tools thoughtfully to accelerate learning and engineering work, explore solutions, improve code quality, and reduce repetitive tasks
• Critically evaluate, test, and validate AI-generated output rather than treating it as inherently correct
• Maintain ownership of all work produced with AI assistance, including its correctness, security, maintainability, and alignment with our engineering standards

What You Have

• Experience in backend, DevOps, or infrastructure engineering roles, ideally in SaaS, PaaS, or IaaS environments
• Familiarity with deployment processes and CI/CD pipelines, including supporting services such as artifact registries and related release infrastructure
• Experience working with Linux in production environments
• Working knowledge of at least one major cloud provider, including AWS, GCP, or Azure
• Experience with infrastructure as code and automation using tools such as Terraform, Pulumi, Ansible, Chef, or similar
• Familiarity with containerization and orchestration technologies such as Docker, Kubernetes, ECS, or Nomad
• Experience scripting or writing code in Bash, Python, Go, or similar languages
• Exposure to infrastructure migrations, high-availability initiatives, or performance optimization efforts
• Familiarity with observability stacks such as Prometheus, Grafana, ELK, OpenTelemetry, or similar tools
• Strong communication skills and a collaborative mindset, with an interest in improving the platforms other engineers rely on every day
• A commitment to building secure, maintainable, and scalable systems
• The ability to approach technical problems thoughtfully, learn from feedback, and know when to ask for help
• Eagerness to learn, take ownership of your work, explore new technologies and approaches, and contribute to continuous improvement 
• The ability to evaluate code and recommendations produced by AI tools critically rather than accepting them at face value
• Experience using—or a demonstrated interest in learning—AI-assisted development tools as part of a responsible engineering workflow
• Sound judgment regarding data privacy, intellectual property, security, and the appropriate use of confidential information when working with AI tools

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