Unstructured is defining the standard for enterprise data transformation in the age of LLMs and generative AI. In just two years, we’ve raised over $65M from world-class investors, including Menlo Ventures, Bain Capital, Databricks, NVIDIA, Microsoft, and IBM.
Our open-source toolkit has been downloaded 52M+ times and is used by 66,000+ companies, including nearly half of the Fortune 500. We power production AI workflows across commercial and federal sectors—transforming PDFs, HTML, Word docs, images, emails, and more into AI-ready data pipelines that scale. We’re not just building tools, we’re building the backbone of generative AI and the infrastructure that unlocks intelligence across industries.
Do you enjoy debugging real production systems and solving hard infrastructure problems? At Unstructured, our customers run dedicated deployments inside their own VPCs, and when things break, you’re the person they rely on.
As a Technical Support Engineer, you’ll work directly with enterprise customers to troubleshoot issues across cloud infrastructure, Kubernetes, networking, and data pipelines. This is not SaaS support, you’ll be operating inside complex, customer-owned environments and partnering closely with Engineering to resolve root causes.
Triage and resolve customer issues across VPC deployments, APIs, and data pipelines
Debug production systems using logs, metrics, and system-level analysis
Reproduce issues and drive them to resolution with Engineering
Help customers operate Unstructured in AWS, GCP, or Azure environments
Troubleshoot Kubernetes, Docker, networking (VPC, private endpoints), and IAM issues
Guide customers on running reliable, production-grade deployments
Investigate issues across document processing pipelines and API behavior
Identify root causes, not just workarounds, and validate fixes
Work closely with Engineering, Forward Deployed Engineers, and Solutions on escalations and blockers
Act as the voice of the customer for enterprise deployments
Build runbooks, troubleshooting guides, and internal tooling
Identify patterns and drive improvements in reliability and supportability
Strong experience with cloud environments (AWS, GCP, or Azure), especially VPC networking
Hands-on experience with Kubernetes and Docker
Proficiency in Python skills for scripting, API integration, and automation
Proven ability to debug production or distributed systems end-to-end
Comfortable working with APIs, logs, and system-level debugging tools
Strong communicator who can work effectively with both engineers and customer teams
High ownership, strong troubleshooting instincts, and ability to operate in ambiguous, fast-moving environments
Experience supporting self-hosted or single-tenant deployments
Familiarity with Terraform, Pulumi or other IaC tools
Experience with observability tools (Datadog, Prometheus, Grafana)
Python or scripting experience for debugging and automation
Exposure to data pipelines, ETL workflows, or AI/LLM systems
Experience working in early-stage or high-growth startups
Real Customer Impact: Work with top global companies solving bleeding-edge AI use cases
Mission-Critical Work: Your solutions will directly power AI deployments in production
Ownership & Autonomy: Be trusted to drive results and innovate from day one
Elite Team: Join world-class builders who value humility, speed, and precision
Strong Benefits: Competitive salary, full health benefits, equity, and parental leave
Ready to help companies unlock the full power of unstructured data?
Apply now to join Unstructured and shape the future of AI delivery.
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