Solutions Architect

• Lead Technical Discovery and Solution Design
• Partner with account executives during customer engagements to uncover requirements, define success criteria, and architect tailored solutions
• Design and present technical architectures that integrate Unstructured’s SDKs, APIs, and connectors into customer environments
• Architect and Validate Complex Deployments
• Implement Unstructured across diverse infrastructure—cloud-native (AWS, GCP, Azure), hybrid, and on-premises
• Design scalable solutions leveraging Kubernetes, containerized workloads, and Python-based data pipelines
• Solve real-world challenges involving file parsing, ETL, vectorization, and retrieval at enterprise scale
• Demonstrate Technical Credibility in the Field
• Deliver compelling demos, proof-of-concepts, and reference architectures that show value and technical rigor
• Act as a trusted advisor to customer architects and data science teams, guiding best practices and integration strategies
• Collaborate Cross-Functionally
• Provide structured, actionable feedback from customer interactions to influence product roadmap decisions
• Partner with engineering and product teams to reproduce issues, validate fixes, and ensure customer success
• Create and Share Best Practices
• Contribute reusable templates, demo assets, and solution guides for internal and external enablement
• Elevate the technical standard across the field org through documentation and peer collaboration

• 7+ years in Solutions Architecture, Sales Engineering, or a customer-facing technical role
• Familiarity with at least 1 Cloud Provider (AWS, Azure, or GCP), and general security and networking principles
• Deep familiarity with Python for scripting, API integration, and building PoCs
• Hands-on understanding of ETL/data pipeline design, RESTful APIs, and data transformation workflows
• Strong grasp of unstructured data processing: text, PDFs, images, and retrieval workflows
• Ability to communicate complex technical concepts clearly to both engineering and executive stakeholders
• Proven record of technical ownership in technical engagements—POCs, architecture reviews, solution validation, and deployment/implementation

Bonus: experience and knowledge of Kubernetes and containerization, and deploying applications to these environments

• Highly Technical Work: You’ll design and deploy real AI/data infrastructure, not just talk about it
• Elite Customers & Impact: Work directly with leading enterprises and federal teams on GenAI deployments
• Cross-Functional Collaboration: Influence product direction and customer strategy in equal measure
• Startup Agility + Enterprise Reach: Move fast, stay hands-on, and solve problems that truly scale
• Backed by the Best: Our investors include Nvidia, Microsoft, IBM, Databricks, and more