Solutions Engineer (US) - Qdrant

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 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.

What you will own

• 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.

Who you are

• 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 validate business value rather than for its own sake.
• Ability to calculate total cost of ownership (TCO) and estimate hardware requirements (RAM, CPU, disk) for distributed systems.
• Experience with Kubernetes and cloud platforms (AWS, GCP, or Azure), and how infrastructure choices affect cost and performance.
• Strong communication skills: comfortable explaining technical concepts to both engineers and business stakeholders.

Nice to have

• Experience with vector databases or search technologies (Elasticsearch, Solr, OpenSearch, Lucene, or similar).
• Exposure to enterprise procurement processes, infosec questionnaires, or MSA redlines.

Why join us

• A remote-first, international team working on cutting-edge AI infrastructure.
• A competitive salary with additional perks.
• Flexible working hours and async-friendly culture.
• High ownership and real impact.
• Open-source, engineering-driven culture.
• Choose your own laptop equipment.
• Comprehensive benefits package including 401k match, health, dental, and vision insurance, plus flexible PTO policy for US-based full-time employees.