Qdrant.Tech
Solutions Engineer (US)
Remote - United States. Posted 2 days ago
The role
You will own the technical side of enterprise deals by leading scoping, pricing, and deployment of search solutions. You will act as a technical authority to design resilient architectures and manage the technical sales workflow.
What you will do
- Translate complex architectural requirements into accurate pricing models and contract terms
- Drive technical sales workflow across Support, Product, and Engineering to unblock POCs
- Identify and mitigate deployment risk such as latency bottlenecks and resource contention
- Lead architectural reviews and migration assessments from legacy search engines
- Design resilient, production-grade high-availability search clusters
- Serve as the primary technical authority and long-term advisor for clients
Required qualifications
- 2-5 years of technical, customer-facing experience in Sales Engineering, Solutions Architecture, or Technical Consulting
- Track record of owning complex, high-value deals independently
- At least 2 years of direct, hands-on vector search experience (Qdrant, Pinecone, Weaviate, Zilliz/Milvus, or similar)
- Strong scripting ability in Python or Bash
- Fluency in calculating total cost of ownership (TCO) and estimating hardware requirements for distributed systems
- Deep expertise in Kubernetes and cloud platforms (AWS, GCP, or Azure)
- Excellent communication skills to influence engineers, VPs, and business stakeholders
Nice to have
- Background in data science, computer engineering, or a previous DevOps/SRE role
- Exposure to enterprise procurement processes, infosec questionnaires, or MSA redlines
Benefits
- Competitive salary
- Additional perks
- Flexible working hours
- Async-friendly culture
- High ownership and real impact
- Open-source, engineering-driven culture
- Choose your own laptop equipment
- 401k match
- Health, dental, and vision insurance
- Flexible PTO policy
About the company
Qdrant is an open-source vector search engine powering AI applications. They are building the retrieval infrastructure layer for modern AI.