Elastic Senior Customer Architect Search 

United States 

385987284

You’ll bring deep hands-on expertise in designing, deploying, and optimizing search platforms—ranging from traditional Elasticsearch-based Enterprise Search to modern semantic and vector search architectures (e.g., embeddings, RAG, hybrid search systems). You should be comfortable operating in cloud-native environments (AWS/Azure/GCP), implementing robust indexing pipelines, tuning search relevance, and scaling for performance and cost-efficiency.

• Architect and implement advanced Enterprise Search , Vector Search , and Semantic/RAG systems for large-scale deployments.
• Develop and implement Technical Success Plans tailored to each customer, covering indexing pipelines, query relevance (e.g., recall@k, latency), vector similarity performance, and adoption metrics.
• Lead the full customer lifecycle: onboarding, proof-of-concept (POC), rollout, adoption, escalation, and expansion.
• Design RAG and semantic search workflows using embedding models (LLM, ELSER, Hugging Face, LangChain, etc.).
• Optimize search relevance and performance: tuning indices, scaling clusters, running vectors, and conducting A/B tests.
• Partner with Sales, Pre‑Sales, Services, and Support to align technical strategy and customer satisfaction.
• Monitor usage, diagnose adoption gaps, and proactively propose expansions and upsells aligned with ARR goals.

• 8–12+ years building and operating enterprise search systems , including vector and semantic search.
• Strong experience with Elastic or similar platforms: Elasticsearch, Pinecone, Qdrant, Milvus, Weaviate.
• Authority in embedding‑based retrieval, LLM integration, RAG pipelines, and vector database architecture.
• Consistent track record of designing scalable, performant search infrastructure on cloud platforms (AWS/Azure/GCP).
• Excellent communicator able to present technical designs and business impact to both technical and executive audiences.
• Data-driven mentality: adept at measuring search performance (e.g., latency, throughput, recall) and acting on insights.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. Previous roles in Solution Architecture, Pre‑Sales Engineering, or Customer Success focused on search/AI applications.

• Hands-on experience with RAG systems , chat/search applications, and open-source contributions.
• Understanding of vector database internals: ANN algorithms, indexing strategies, recall/precision evaluation.
• Familiarity with embedding model tuning and search relevance optimization frameworks.

We strive to have parity of benefits across regions, and while regulations differ from place to place, we believe taking care of our people is the right thing to do.

• Competitive pay based on the work you do here and not your previous salary
• Health coverage for you and your family in many locations
• Ability to craft your calendar with flexible locations and schedules for many roles
• Generous number of vacation days each year
• Increase your impact - We match up to $2000 (or local currency equivalent) for financial donations and service
• Up to 40 hours each year to use toward volunteer projects you love
• Embracing parenthood with a minimum of 16 weeks of parental leave

Applicants have rights under Federal Employment Laws and can view the following posters linked below:

Elasticsearch develops and distributes technology and information that is subject to U.S. and other country export controls and licensing requirements for individuals who are located in or are nationals of the following sanctioned countries and regions: Belarus, Cuba, Iran, North Korea, Russia, Syria, the Crimea Region of Ukraine, the Donetsk People’s Republic (“DNR”), and the Luhansk People’s Republic (“LNR”). If you are located in or are a national of one of the listed countries or regions, an export license may be required as a condition of your employment in this role. Please note that national origin and/or nationality do not affect eligibility for employment with Elastic

Compensation for this role is in the form of base salary plus a variable component, that together comprise the On-Target Earnings (OTE). On-Target Earnings (OTE) are based on a 70/30 pay mix (base salary / target variable).

The typical starting OTE range for new hires in this role is listed below. This range represents the lowest to highest OTE we reasonably and in good faith believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the range may be modified in the future.

An employee's position within the OTE range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs.

The typical starting salary range for this role is:

$107,500—$170,100 USD

The typical starting Target Variable range for this role is:

$46,000—$72,800 USD

The typical starting On-Target Earnings (OTE) range for this role is:

$153,500—$242,900 USD