Field Infrastructure Engineer

unstructured.io
Summary
Join Unstructured, a company building open-source and commercial tools for data preprocessing and transformation for AI/ML pipelines, as a Field Infrastructure Engineer. This role involves providing deployment expertise, scaling, and support of the platform across various customer enterprise environments. You will work closely with users, ensuring resilient, high-performance implementations. The position requires collaboration with customer Engineering and Infrastructure teams and working with a modern tech stack (Python, Kubernetes, Helm, CI/CD). You will provide critical product feedback, influence infrastructure decisions, and contribute to reliability across the growing customer base. Ideally, this position is based in San Francisco, but flexibility is possible for exceptional candidates. This is an opportunity to work on impactful problems at the intersection of data and AI within a supportive, high-performance team culture.
Requirements
- 8+ years of experience in an SRE, DevOps, or Infrastructure Engineering role, ideally with experience on customer-facing or field-deployment work
- Deep expertise in cloud platforms (AWS, GCP, or Azure)
- Hands-on experience with Kubernetes, Docker, and container orchestration
- Strong skills in Linux systems, networking, and scripting (e.g., Bash, Python, Go)
- Proficiency with Infrastructure-as-Code (Terraform, CloudFormation, Ansible, etc.)
- Familiarity with monitoring, logging, and observability practices and tools
- Experience supporting production systems and operating in high-scale environments
- Good communication skills
Responsibilities
- Support customer implementations by deploying, configuring, and troubleshooting infrastructure directly in customer environments
- Act as a technical expert and point of contact during customer engagements, collaborating with Customer Success and our Core Engineering teams
- Design and implement highly available, scalable, and observable systems across customer environments
- Use tools like Terraform, Pulumi etc to build reusable CI/CD pipelines
- Maintain and optimize Kubernetes clusters, container orchestration, and service mesh configurations
- Guide customers on configuring monitoring and alerting frameworks for performance, reliability, and uptime (e.g., Elastic, Prometheus, Grafana, Datadog)
- Improve developer velocity through tooling, automation, and infrastructure improvements
- Support incident response, root cause analysis, and blameless postmortems
- Partner with engineering teams on production readiness, capacity planning, and rollout strategies
Preferred Qualifications
- Experience with machine learning infrastructure or data pipeline systems
- Exposure to serverless or event-driven architectures
- Contributions to open source projects or DevOps communities
- Familiarity with security best practices for cloud-native environments
Benefits
- Competitive salary, equity, and benefits package
- Supportive, high-performance team culture