Senior Solutions Engineer (APAC)
Q
QdrantAI Infrastructure
Remote - Australia, Remote - India, Remote - Singapore, Remote - Japan, APAC time-zone overlapFull-TimeSenior
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Experience
- 5+ years
- Required Skills
- Cloud ComputingKubernetesDistributed Systems
Requirements
- 5+ years of pre-sales or solutions engineering experience, ideally with a background in data infrastructure or systems architecture.
- 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.
- Hands-on experience with RAG (retrieval-augmented generation) pipelines.
- Working knowledge of the modern AI stack, including LLMs, embedding models, and agentic frameworks.
- Working knowledge of structured sales qualification frameworks like MEDDICC/MEDDPICC.
- Ability to articulate technical indexing trade-offs to engineers and infrastructure ROI to CIOs.
- Experience with vector search, approximate nearest neighbor algorithms, or semantic retrieval systems (Nice to have).
- Background with Rust, C++, or other systems languages (Nice to have).
- Familiarity with deployment patterns including Kubernetes, hybrid cloud, on-prem, or air-gapped environments (Nice to have).
Responsibilities
- 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.
- 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, demonstrating performance advantages over JVM-based or proprietary alternatives.
- Serve as a trusted advisor on AI infrastructure decisions, helping customers navigate migration from legacy databases and deployment across cloud, on-prem, or air-gapped environments.
- Contribute to the field engineering knowledge base including reference architectures, technical guides, and reusable POC frameworks.
View Full Description & ApplyYou'll be redirected to the employer's site
