Strategic Customer Solutions Architect (amer)

Supabase Supabase · Data AI · AMER · Growth

This role focuses on architecting and optimizing AI-native applications for enterprise customers using Supabase's Postgres platform, with a specific emphasis on vector storage, embedding pipelines, and similarity search. The Solutions Architect will partner with customers on AI workloads, guide them through complex technical challenges, and ensure reliable performance at scale.

What you'd actually do

  1. Build and maintain deep, trust-based relationships with senior technical and executive stakeholders across a focused portfolio of strategic accounts.
  2. Partner with customers operating at significant scale to ensure their systems perform reliably under production load.
  3. Serve as the resident Postgres expert for your accounts.
  4. Guide customers through Supabase's enterprise security capabilities, including Row Level Security (RLS) policy design, audit logging, SOC 2 and HIPAA compliance requirements, and encryption best practices.
  5. Partner with customers building AI-native applications on Supabase.

Skills

Required

  • Solutions Architecture
  • Database Engineering
  • PostgreSQL internals
  • performance tuning
  • replication
  • extensions
  • schema design
  • complex database migrations
  • AI application architecture
  • vector databases
  • embedding pipelines
  • similarity search
  • systems at significant scale
  • high-throughput, high-availability workloads
  • enterprise security
  • compliance requirements
  • Row Level Security
  • SOC 2
  • HIPAA
  • audit logging
  • encryption standards
  • web application development
  • Python
  • C#
  • JavaScript frameworks
  • Node.js
  • managing senior executive relationships
  • navigating complex, multi-stakeholder enterprise environments
  • communication skills

Nice to have

  • pgvector or similar vector storage solutions
  • self-hosted or BYO cloud infrastructure deployments
  • HubSpot
  • BigQuery
  • revenue and analytics tooling

What the JD emphasized

  • mission-critical, highly scaled workloads
  • senior technical and executive stakeholders
  • complex technical challenges
  • real production pressure
  • complex platform-level issues
  • complex performance bottlenecks
  • push the boundaries of what they can build on Postgres and Supabase
  • enterprise security capabilities
  • compliance requirements
  • Large-Scale Migrations
  • multi-stakeholder environments
  • AI-native applications
  • production-grade AI systems
  • deep technical credibility
  • high-complexity workloads
  • Expert-level knowledge of PostgreSQL
  • significant scale — high-throughput, high-availability workloads
  • enterprise security and compliance requirements
  • senior executive relationships
  • complex, multi-stakeholder enterprise environments

Other signals

  • AI-native applications
  • vector storage architecture
  • embedding pipeline design
  • similarity search optimization
  • scalable, production-grade AI systems