Software Engineer, Infrastructure

Serval is an AI-native automation platform transforming how enterprises operate. We build intelligent agents that understand real-world workflows and execute them end-to-end — replacing manual processes and rigid legacy systems with adaptive, learning software. Founded in early 2024, Serval is already trusted by companies like Fox, Notion, Perplexity, Vercel, and Brex to automate high-volume, high-friction operational work across their organizations.
At the core of Serval is an agentic AI platform that turns natural language into production-grade workflows. Our agents don’t just respond to requests — they reason, take action across systems, and continuously improve with usage. What began with operational use cases has quickly evolved into a horizontal AI automation layer used across IT, HR, Finance, Security, Legal, and Engineering.
Our mission is to eliminate repetitive, manual work across the enterprise and give teams leverage through intelligent automation. Long term, we’re building the universal AI operations layer — a system of agents that sits across business functions and runs the workflows that keep modern companies moving.
We’re backed by leading investors including Sequoia Capital, Redpoint Ventures, Meritech, First Round, General Catalyst, Elad Gil, and others, and founded by product and engineering leaders from Verkada.

Serval is building an AI platform to automate complex IT workflows for modern enterprises. As a Software Engineer, Infrastructure, you'll build and scale the foundational systems that power Serval's AI agents and workflow automation platform. A critical part of this role is enabling and supporting self-hosted deployments for enterprise customers who require on-premises or private cloud installations. This role is for engineers with deep expertise in distributed systems, infrastructure-as-code, production operations, and customer-facing infrastructure support who want to shape the technical architecture of a fast-growing platform.

• Design, implement, and operate large-scale distributed systems that power Serval's AI agents, workflow orchestration, and data pipelines.

• Write and maintain Terraform modules to provision and manage cloud infrastructure across AWS, GCP, or Azure environments.

• Build and maintain deployment packages, installation scripts, and infrastructure templates that enable customers to self-host Serval in their own environments.

• Provide technical guidance and troubleshooting support to enterprise customers deploying and operating self-hosted instances of Serval.

• Ensure high availability, performance, and reliability of production systems through monitoring, alerting, incident response, and capacity planning.

• Build internal tools and platforms that enable product engineers to deploy, test, and operate services efficiently.

• Collaborate with engineering teams to design resilient, scalable architectures that support both cloud-hosted and self-hosted deployment models.

• Profile and optimize system performance, including compute, storage, networking, and database layers.

• Implement security best practices and ensure infrastructure meets enterprise compliance requirements for both managed and self-hosted deployments.

• 3+ years building and operating large-scale distributed systems in production environments.

• Strong experience writing and maintaining Terraform for infrastructure provisioning and management.

• Deep knowledge of at least one major cloud provider (AWS, GCP, or Azure), including compute, networking, storage, and managed services.

• Experience building, packaging, and supporting self-hosted or on-premises software deployments for enterprise customers.

• Proficiency in Python, Go, or similar languages for building automation, tooling, and infrastructure services.

• Strong understanding of networking, databases, containerization (Docker, Kubernetes), and orchestration systems.

• Experience with monitoring, logging, alerting, and incident management tools (e.g., Datadog, Prometheus, Grafana, PagerDuty).

• Ability to communicate technical concepts clearly to customers and provide infrastructure support and guidance.

• Ability to debug complex system issues, analyze performance bottlenecks, and implement effective solutions.

• Experience with Kubernetes in production, including cluster management and workload orchestration.

• Background in CI/CD systems, build pipelines, and deployment automation.

• Experience with workflow orchestration systems such as Temporal, including long-running workflows, retries, and failure handling.

• Experience with data infrastructure (streaming systems like Kafka, data warehouses, ETL pipelines).

• Knowledge of security and compliance frameworks (SOC 2, ISO 27001, GDPR).

• Experience supporting enterprise customers with complex deployment requirements.

• Previous work at a high-growth startup or experience scaling infrastructure rapidly.

• Impact: Be a key player in shaping the success of our product and company.

• Growth: Build a fundamentally new AI product offering with the support of our experienced team and investors. Grow rapidly with the company.

• Culture: Join a culture that values innovation, ownership, accountability, and fun.