Senior Solutions Engineer

What you will own:

• Own the technical strategy in enterprise deals from first call to production deployment, partnering with Account Executives to qualify, architect, and close for our entire Asian-Pacific client base

• Act as a Technical Account Manager for a small portfolio of existing enterprise customers in the region alongside active prospects, identifying new use cases, expansion opportunities, and upsell paths, and looping in Account Executives and internal resources to advocate for the customer.

• Design vector search architectures for high-scale workloads, including multi-tenant agentic systems, hybrid search pipelines, and low-latency retrieval at billion-vector scale .

• Build proof-of-concept systems that customers take to production (not throw away), demonstrating Qdrant's performance advantages over JVM-based or proprietary alternatives.

• Serve as a trusted advisor on AI infrastructure decisions, helping customers navigate migration from legacy databases, avoid architectural lock-in, and deploy across cloud, on-prem, or air-gapped environments.

• Contribute to the field engineering knowledge base: reference architectures, technical guides, and reusable POC frameworks that scale the team's impact.

Who you are

• 5+ years of pre-sales or solutions engineering, ideally with a background in data infrastructure or systems architecture. Hands-on infrastructure depth alone isn't enough, we need a proven track record running technical qualification and proof-of-concept processes within a live sales cycle.

• Experience designing or operating distributed systems, search infrastructure, or data pipelines at production scale.

• Ideally, hands-on experience with RAG (retrieval-augmented generation) pipelines specifically, plus working knowledge of the broader modern AI stack ( LLMs, embedding models, agentic frameworks ).

• Ideally, working knowledge of a structured sales qualification framework such as MEDDICC/MEDDPICC , and the ability to apply it in real deal conversations, connecting technical decisions to business outcomes and deal strategy.

• Strong communicator across audiences: you can go deep on indexing trade-offs with a Staff Engineer and explain infrastructure ROI to a CIO in the same afternoon.

Nice to have

• Experience with vector search , approximate nearest neighbor algorithms, or semantic retrieval systems.

• Background with Rust, C++ , or other systems languages.

• Familiarity with deployment patterns: Kubernetes, hybrid cloud, on-prem, or air-gapped environments .

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.

For US-based candidates, we also offer a comprehensive benefits package including 401k match, health, dental, and vision insurance , plus flexible PTO policy.