Job description
Unstructured builds open-source and commercial tools that enable developers to preprocess and transform unstructured data — PDFs, HTML, Word docs, images, and more — for AI/ML pipelines. Our solutions power production-grade, scalable generative AI use cases at leading enterprises.
We’re a team of builders obsessed with performance, simplicity, and reliability. If you’re excited by complex systems, cutting-edge ML infrastructure, and high-impact problems, we’d love to meet you.
We’re looking for a Field Infrastructure Engineer to provide deployment expertise, scaling, and support of our platform across a range of customer enterprise environments. Working closely with our users, this role is essential to delivering resilient, high performance implementations in the field, and will collaborate closely with customer Engineering and Infrastructure teams.
As a Field Infrastructure Engineer, you’ll work across a modern stack (Python, Kubernetes, Helm, CI/CD with GitHub Actions, etc.), provide critical product feedback, influence infrastructure decisions, and help shape reliability across our growing customer base.
***Ideally based in San Francisco to join our founding engineering office team 3x/week, but open to flexibility for exceptional candidates.***
What You’ll Do
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.
What We’re Looking For
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.
Bonus Points
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.
Why Join Us?
Opportunity to own critical infrastructure at a fast-growing company.
Work on impactful problems at the intersection of data and AI.
Competitive salary, equity, and benefits package.
Supportive, high-performance team culture.
