Database Support Engineer
PhoenixAI
Database Support Engineer
PhoenixAI
Real-time analytical database for AI agents
About PhoenixAI
PhoenixAI is the Agentic AI Database, purpose-built to give autonomous AI agents sub-second access to live enterprise data at massive scale. The platform unifies real-time and at-rest data in a single AI-native engine, combining the speed and concurrency that agentic workloads demand with the governance and deployment flexibility enterprises require to put AI into production. Formerly known as CelerData, PhoenixAI is headquartered in Menlo Park, California. Learn more at phoenixdata.ai
We are seeking a talented Database Support Engineer to join our team and play a pivotal role in the sales cycle for our Agentic Database. You will be working on the post-sales side — driving onboarding, deployment, adoption, and long-term customer success. This customer-facing role requires a blend of deep technical expertise, strong communication skills, and a passion for solving complex data challenges throughout the customer journey.
As a Database Support Engineer, you'll be the ongoing technical point of contact for customers, ensuring they realize sustained value from PhoenixAI's Agentic Database. Your responsibilities include:
Every PhoenixAI hire is held to the same operating bar: own the outcome, seek truth and build trust, move fast with judgment, work AI-first, and raise the bar without ego.
The base salary range for this role in Singapore is SGD$150,000 to SGD$180,000. The offer also includes equity and PhoenixAI's full benefits package. Where you land in the range depends on your experience, scope, and interview results.
PhoenixAI is an equal opportunity employer. We welcome candidates of all backgrounds and do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic.
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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.
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