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PhoenixAI

Real-time analytical database for AI agents

Presales Solutions Architect

Pre-Sales Solution EngineeringConfirmed live in the last 24 hours
Full-timeMenlo Park, CA, USAHybrid

About the Job

Requirements

  • Have 3 or more years of experience in a presales, solutions engineering, or technical consulting role, ideally within data analytics, databases, or cloud infrastructure.
  • Have hands-on experience with OLAP workloads, query optimization, and data modeling, such as star and snowflake schemas.
  • Be proficient in SQL.
  • Have a deep understanding of distributed data processing system theory.
  • Be familiar with at least one public cloud platform: AWS, GCP, or Azure.
  • Be able to explain complex technical concepts clearly to diverse stakeholders, from engineers to C-level executives.
  • Be able to troubleshoot technical challenges during proof-of-concepts and adapt solutions to customer needs.
  • Have experience supporting sales teams in technical evaluations, with a track record of securing technical wins and driving revenue growth.

Responsibilities

  • Partner with the sales team to guide prospects through technical evaluations, deliver presentations and demonstrations, architect tailored solutions, and secure technical wins.
  • Demonstrate the product’s capabilities, including its vectorized query engine, lakehouse analytics, and multi-table joins for agentic AI workloads, through presentations, customized demos, and proof-of-concepts.
  • Work with prospects to understand needs such as data scale, latency, and integrations, and architect solutions based on the product.
  • Lead the design, implementation, and optimization of proof-of-concepts so prospects can evaluate the product’s performance and usability.
  • Maintain detailed evaluation records covering use cases, challenges, proof-of-concept plans, and outcomes to improve processes and inform product enhancements.
  • Collaborate with sales to align technical discussions with business goals, address objections, close deals, and share customer insights with product and engineering teams to shape the product roadmap.
  • Deliver webinars, staff conference booths, speak at user groups, and write blogs about agentic AI use cases and best practices.

Desired Qualifications

  • Knowledge of business intelligence tools such as Tableau or Looker.
  • Experience with streaming processing systems such as Kafka or Redpanda.

About the Company

PhoenixAI

Real-time analytical database for AI agents

PhoenixAI builds real-time analytic databases for AI agents and applications. Its engine ingests streaming data (Kafka, Flink CDC) and reads lakehouse tables (Iceberg, Delta Lake, Hudi) in place, then joins fresh data with historical data in a single query to deliver sub-second SQL without precomputation. It offers isolated multi-warehouse compute so agent workloads, BI, and data ingestion run side-by-side without competition for resources, with monitoring, security, and access controls. Customers can use a cloud-hosted managed version (PhoenixAI Cloud) deployed in their cloud account, or a self-managed Kubernetes version (PhoenixAI Anywhere) in their environment. The company centers its product on an open-source core (StarRocks) and adds extra security, governance, and support under commercial contracts. The goal is to provide fast, reliable, and secure real-time analytics for AI workloads and data teams, enabling seamless querying across streaming and historical data.

Company size
51-200
Company stage
Series B
Total funding
$80M
Headquarters
Menlo Park, CA
Founded
2022

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