← All Positions
Solutions Engineer
Job Summary
Join a dynamic early-stage startup as a Solutions Engineer, bridging cutting-edge document intelligence technology with enterprise customers. In this highly technical, customer-facing role, you will partner with sales teams to drive deals through technical discovery, demos, and production deployments. Your expertise will ensure customer success while collaborating with engineering teams to refine the platform based on real-world feedback.
Essential Functions
- Partner closely with Account Executives throughout the sales cycle, owning technical discovery, demos, and evaluations
- Deploy and configure extraction pipelines within customer environments, supporting pilots and production rollouts
- Diagnose and resolve accuracy, latency, and infrastructure issues across distributed systems for enterprise customers
- Build internal tools and customer-facing utilities in Python to support integrations and downstream workflows
- Collaborate with ML, platform, and product teams to surface customer feedback and improve the platform
- Serve as the go-to technical expert in the sales process to drive deals forward
Required Qualifications
- 3-4+ years in a pre-sales Solutions Engineering or Forward Deployed Engineering role at a technical B2B company
- Strong familiarity with sales processes such as MEDDIC or Command of the Message
- Hands-on experience with APIs, distributed systems, and production infrastructure
- Proficiency in Python for tooling, automation, and backend integrations
- Customer-facing experience required; pure software engineering backgrounds without client interaction will not be considered
- Adaptable with ability to build strong relationships with account executives
Preferred Qualifications
- 3-7 years in customer-facing technical roles like Solutions Engineer, Forward Deployed Engineer, or Implementation Engineer at a technical SaaS company
- Experience at an early-stage startup (Seed-Series B); Big Tech experience acceptable if paired with startup and B2B focus
- Background in data infrastructure, ML platforms, or document processing systems
- Experience with Kubernetes
- Familiarity with API extraction and integration in infrastructure settings
Technical Skills
- Solutions Engineering
- Forward Deployed Engineering
- APIs
- Distributed systems
- Production infrastructure
- Kubernetes
- Python
- Tooling and automation
- Backend integrations
- Sales processes (MEDDIC, Command of the Message)
Education & Certifications
Bachelor's degree in Computer Science, Engineering, or a related technical field.
Compensation & Benefits
Competitive base salary in the range of $180,000 - $200,000 annually, depending on experience. Additional benefits typical for a fast-growing technology startup.