Remote-First Enterprise Solutions Engineer: Vector AI Search

Qdrant; San Francisco (CA); Remote; USD 140,000 - 200,000; Full time

Benefits offered by this job

401k match

Health, dental, vision insurance

Flexible PTO

Remote-first international team

Open-source culture

Choose your own laptop

Job summary

Qdrant is seeking a Solutions Engineer to own the technical side of enterprise deals, leading scoping, pricing, and deployment of semantic search, image and video search, and on-premise and edge deployments for complex customers. This remote-first role partners with Account Executives as the technical authority, driving POCs and architectural migrations from Elastic/Solr/OpenSearch to Qdrant.

You will design resilient, production-grade architectures, translate requirements into contracts, and

Qualifications

• 2-5 years of technical, customer-facing experience in Sales Engineering, Solutions Architecture, or Technical Consulting, with a track record of owning complex, high-value deals independently, including at least 2 years of direct, hands-on vector search experience.
• Strong scripting ability in Python or Bash, used to build reusable tools and validate business value at scale, not just one-off scripts.
• Fluency in calculating total cost of ownership (TCO) and estimating hardware requirements (RAM, CPU, disk) for distributed systems, including for multi-region or highly regulated deployments.
• Deep expertise in Kubernetes and cloud platforms (AWS, GCP, or Azure), with a clear point of view on how infrastructure choices affect cost and performance at scale.
• Excellent communication skills, comfortable running the room with engineers, VPs, and business stakeholders alike, and able to influence without authority across internal teams.

Responsibilities

• Own Technical-to-Commercial Strategy: Translate complex architectural requirements (multi-AZ, sharding, replication) into accurate pricing models and contract terms, independently protecting deal value in high-stakes negotiations.
• Drive Deal Execution End to End: Own the technical sales workflow across Support, Product, and Engineering to unblock POCs, resolving cross-functional bottlenecks without escalation.
• Identify and Mitigate Deployment Risk: Proactively spot noisy neighbor issues, latency bottlenecks, and resource contention before they threaten renewals or expansions, and advise customers on architectural fixes.
• Lead Architectural Reviews and Migration Assessments: Run discovery sessions solo, validate use cases, and design migration paths from legacy search engines like Elastic, Solr, and OpenSearch to Qdrant.
• Design Resilient, Production-Grade Architecture: Spec high-availability search clusters that meet demanding customer SLAs and throughput requirements, including for the most technically complex accounts.
• Own Client Trust at the Executive Level: Serve as the primary technical authority during evaluation, guiding customers to value quickly and acting as a long-term advisor beyond the initial sale.

Skills

Vector search

Scripting (Python/Bash)

Cost modeling & TCO

Kubernetes

Cloud platforms (AWS/GCP/Azure)

Communication / stakeholder influence

Tools

Kubernetes

AWS

GCP

Azure

Job description

Qdrant is seeking a Solutions Engineer to own the technical side of enterprise deals, leading scoping, pricing, and deployment of semantic search, image and video search, and on-premise and edge deployments for complex customers. This remote-first role partners with Account Executives as the technical authority, driving POCs and architectural migrations from Elastic/Solr/OpenSearch to Qdrant.

You will design resilient, production-grade architectures, translate requirements into contracts, and