Solutions Engineer (US)

About the role

Qdrant is an open-source vector search engine powering the next generation of AI applications, from semantic search and retrieval-augmented generation (RAG) to AI agents and real-time recommendations. Trusted by global leaders like Canva, HubSpot, Tripadvisor, Bosch, and Deutsche Telekom, we’re building the retrieval infrastructure layer for modern AI. Recently raising $50M in Series B funding, we are growing rapidly and committed to transforming how AI understands and interacts with data. As a remote-first company, we believe diverse backgrounds, perspectives, and experiences fuel innovation. Here, you’ll own meaningful work, tackle challenges, and grow alongside passionate individuals dedicated to shaping the future of AI. As a Solutions Engineer, you'll take ownership from day one, acting as a technical guide for our clients. We're looking for someone with a strong builder mindset who's self-reliant and truly passionate about vector search. An entrepreneurial streak will set you up for success in this role.

Responsibilities

• Support the Technical-to-Commercial Translation: Help translate architectural requirements (Multi-AZ, sharding, replication) into accurate pricing models and contract terms, working alongside senior team members to protect deal value.
• Help Drive Deal Execution: Coordinate with Support, Product, and Engineering to unblock proofs of concept (POCs), and keep the technical sales workflow moving in Jira and Salesforce.
• Flag Deployment Risks Early: Learn to spot noisy neighbour issues, latency bottlenecks, and resource contention before they affect renewals or expansions.
• Support Architectural Reviews and Migration Assessments: Join discovery sessions to help validate use cases and map migration paths from legacy search engines like Elastic, Solr, and OpenSearch to Qdrant.
• Contribute to Resilient Architecture Design: Help spec high-availability search clusters that meet customer SLAs and throughput needs.
• Build Trust with Client Stakeholders: Act as a technical point of contact during the evaluation process, helping customers reach value quickly.

Requirements

• 2-4 years of technical, customer-facing experience in Sales Engineering, Solutions Architecture, or Technical Consulting.
• Background in data science, computer engineering, or a previous DevOps role.
• Scripting ability in Python or Bash, used to