
51 - 200 employees
Founded 2021
đ¤ Artificial Intelligence
âď¸ SaaS
Artificial Intelligence ⢠SaaS
Qdrant is a company that builds a highâperformance vector database and managed cloud services for similarity search and AI retrieval. It offers an openâsource, Rustâbased vector engine (Qdrant Vector Database) plus managed offerings (Qdrant Cloud, Hybrid Cloud, Private Cloud, Edge, and Enterprise solutions), optimized for realâtime indexing, hybrid dense+sparse search, multivector retrieval, and largeâscale production deployments. Qdrant is positioned for builders of RAG, semantic search, recommendation systems, AI agents, and anomaly detection, and emphasizes developer APIs, enterprise security/compliance (SOC2, HIPAA options), and deployment flexibility (onâprem, cloud, hybrid, edge).
đ September 22
đşđ¸ United States â Remote
â° Full Time
đ˘ Junior
đĄ Mid-level
đť Solutions Engineer
đŤđ¨âđ No degree required
đť Ghost score 10%
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51 - 200 employees
Founded 2021
đ¤ Artificial Intelligence
âď¸ SaaS
Artificial Intelligence ⢠SaaS
Qdrant is a company that builds a highâperformance vector database and managed cloud services for similarity search and AI retrieval. It offers an openâsource, Rustâbased vector engine (Qdrant Vector Database) plus managed offerings (Qdrant Cloud, Hybrid Cloud, Private Cloud, Edge, and Enterprise solutions), optimized for realâtime indexing, hybrid dense+sparse search, multivector retrieval, and largeâscale production deployments. Qdrant is positioned for builders of RAG, semantic search, recommendation systems, AI agents, and anomaly detection, and emphasizes developer APIs, enterprise security/compliance (SOC2, HIPAA options), and deployment flexibility (onâprem, cloud, hybrid, edge).
⢠Translate architectural requirements such as Multi-AZ, sharding, and replication into accurate pricing models and contract terms ⢠Work alongside senior team members to protect deal value ⢠Coordinate with Support, Product, and Engineering to unblock proofs of concept (POCs) ⢠Keep the technical sales workflow moving in Jira and Salesforce ⢠Identify noisy neighbour issues, latency bottlenecks, and resource contention before they affect renewals or expansions ⢠Join discovery sessions to validate use cases and map migration paths from Elastic, Solr, and OpenSearch to Qdrant ⢠Help specify high-availability search clusters meeting customer SLAs and throughput needs ⢠Act as a technical point of contact during customer evaluations ⢠Help customers reach value quickly
⢠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 ⢠Ability to calculate total cost of ownership (TCO) ⢠Ability to estimate hardware requirements (RAM, CPU, disk) for distributed systems ⢠Experience with Kubernetes ⢠Experience with cloud platforms (AWS, GCP, or Azure) ⢠Understanding of how infrastructure choices affect cost and performance ⢠Strong communication skills, comfortable explaining technical concepts to engineers and business stakeholders ⢠Experience with vector databases or search technologies such as Elasticsearch, Solr, OpenSearch, Lucene, or similar ⢠Exposure to enterprise procurement processes, infosec questionnaires, or MSA redlines
⢠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 ⢠401k match for US-based full-time employees ⢠Health insurance for US-based full-time employees ⢠Dental insurance for US-based full-time employees ⢠Vision insurance for US-based full-time employees ⢠Flexible PTO policy for US-based full-time employees ⢠Remote-first, international team
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