Job Overview  

We are seeking a talented Solutions Architect to join our team and play a pivotal role in the sales cycle for our Agentic Database. You'll partner with our sales team to guide prospects through the technical evaluation of PhoenixAI, delivering compelling presentations or demos, architecting tailored AI-native solutions, and securing technical wins — and then continue as the customer's trusted technical partner post-close, driving successful onboarding, adoption, and long-term 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.

Key Responsibilities  

As a Solutions Architect, you'll be the ongoing technical point of contact for customers, ensuring they realize sustained value from PhoenixAI's Agentic Database, while flexibly supporting the sales team as presales needs arise. Your responsibilities include:

Postsales (primary focus): 

• Onboarding & Deployment: Guide new customers through implementation and deployment, ensuring solutions architected during the sales cycle are realized in production.
• Adoption & Expansion: Serve as the ongoing technical point of contact post-sale, driving product adoption, resolving technical issues, and identifying opportunities for expansion.
• Customer Advocacy: Build long-term relationships with customer technical stakeholders, supporting renewals and acting as their advocate internally.
• Technical Health & Optimization: Proactively monitor account technical health, troubleshoot production issues, and recommend architecture or configuration improvements as customer needs evolve.

Presales (ad hoc support):

• Technical Advocacy: Act as a trusted advisor, demonstrating PhoenixAI’s capabilities—like its vectorized query engine, lakehouse analytics, and multi-table joins for agentic AI workloads—via presentations, customized demos, and Proof of Concept (PoC).
• PoC Support: Assist with the design or execution of Proof of Concepts for prospects when presales bandwidth requires it.

Cross-Cutting:

• Documentation: Keep detailed records of evaluations—covering use cases, challenges, PoC plans, and outcomes—to refine our process and inform product enhancements to PhoenixAI’s Agentic Database.
• Cross-Functional Partnership: Collaborate with sales to align technical discussions with business goals, address objections, and close deals, while gathering customer insights to shape PhoenixAI’s Agentic Database roadmap with product and engineering teams.
• Marketing Support & Thought Leadership: Boost PhoenixAI’s presence by delivering webinars, staffing conference booths, speaking at user groups, and writing blogs on Agentic AI use cases and best practices.

Qualifications  

• Ambition & Curiosity: A driven, inquisitive mindset—eager to learn PhoenixAI Agentic Database product’s intricacies, tackle tough challenges, and grow into the role, even if starting with less experience or specific skills.
• Experience: 5+ years in a post-sales and/or pre-sales role such as solutions engineering, technical consulting or customer success engineering, ideally within the data analytics, database, or cloud infrastructure space.  
• Technical Expertise:  
• • Hands-on experience of OLAP workloads, query optimization, and data modeling (e.g., star schema, snowflake schema)
  • Proficiency in SQL.  
  • Deep understanding of distributed data processing system theory.
  • Familiar with at least one of the public cloud platforms (AWS, GCP, Azure)
• Communication Skills: Proven ability to distill complex technical concepts into clear, compelling narratives for diverse stakeholders, from engineers to C-level executives.
• Problem-Solving: Adept at troubleshooting technical challenges during PoCs and adapting solutions to meet unique customer needs.  
• Sales & Customer Success Mindset: Experience supporting sales and post-sales teams in technical evaluations, with a track record of securing technical wins and driving revenue growth.  
• Bonus Points:  
• • Knowledge of BI tools (e.g., Tableau, Looker)
  • Experience with streaming processing systems (Kafka, Redpanda, etc.)