Presales Solutions Architect, Agentic Data Platform

PhoenixData AI, Inc.; Menlo Park (CA); In loco; USD 150.000 - 200.000; Tempo pieno

Vantaggi offerti da questo lavoro

Bonus

Equity

Benefits package

Descrizione del lavoro

PhoenixAI, the Agentic AI Database, is seeking a Presales Solutions Architect in the San Francisco Bay Area. You’ll partner with the sales team to guide prospects through technical evaluations, deliver compelling presentations or demos, and architect tailored AI-native solutions.

Responsibilities include technical advocacy, solution design, PoC execution, documentation, cross-functional collaboration, and marketing support. Strong SQL, OLAP, and cloud familiarity preferred.

Competenze

• 3+ years in a pre-sales, solutions engineering, or technical consulting role.
• Hands-on experience with OLAP workloads, query optimization, and data modeling.
• Proficiency in SQL.
• Familiar with at least one public cloud platform (AWS, GCP, Azure).
• Ability to distill complex technical concepts for diverse stakeholders.

Mansioni

• Technical advocacy through presentations, demos, and PoCs.
• Architect PhoenixAI-based solutions to meet customer needs.
• Lead PoC design, implementation, and optimization.
• Maintain documentation of evaluations, use cases, and outcomes.
• Collaborate with sales and product/engineering teams on roadmap.
• Support marketing with webinars, booths, and thought leadership.

Conoscenze

Ambition & curiosity

Communication skills

Problem-solving

Sales mindset

Team collaboration

Strumenti

SQL

Kafka

AWS

GCP

Azure

Descrizione del lavoro

PhoenixAI, the Agentic AI Database, is seeking a Presales Solutions Architect in the San Francisco Bay Area. You’ll partner with the sales team to guide prospects through technical evaluations, deliver compelling presentations or demos, and architect tailored AI-native solutions.

Responsibilities include technical advocacy, solution design, PoC execution, documentation, cross-functional collaboration, and marketing support. Strong SQL, OLAP, and cloud familiarity preferred.