Senior Platform Engineer

About The Role

As a Senior Platform Engineer at Equiforte, you will build and scale the core infrastructure that powers our AI-native financial reporting platform. You'll work at the intersection of distributed systems, data engineering, and financial domain logic — designing systems that process millions of financial records with the precision that institutional investors demand.

Engineering | New York | Full-time

• Design and build the data ingestion pipelines that connect to fund administrators, market data providers, and portfolio company data sources
• Architect and implement the platform's core services — including the reporting engine, calculation framework, and API layer
• Own the reliability and performance of production systems handling sensitive financial data for private capital firms managing $10B+ in AUM
• Collaborate with ML engineers to deploy and serve AI models in production with low-latency inference and high availability
• Drive technical decisions on architecture, tooling, and infrastructure with a focus on correctness, observability, and operational simplicity
• Mentor junior engineers and contribute to engineering culture through code reviews, design documents, and knowledge sharing

This role reports to the VP of Engineering and works closely with the ML Engineering and Product teams.

• 5+ years of professional software engineering experience
• Strong proficiency in Type Script/JavaScript and Node.js
• Experience designing and operating distributed systems on AWS (ECS, Lambda, RDS, SQS, or equivalent)
• Deep understanding of relational databases (PostgreSQL preferred) including query optimization and schema design
• Experience building data pipelines that process large volumes with high reliability
• Track record of owning production services end-to-end — from design through deployment and on-call
• Strong written communication skills — we make decisions through design documents and async discussion

• Experience in financial services, fintech, or fund administration
• Familiarity with private capital concepts (NAV, waterfalls, capital calls, IRR)
• Experience with ML model serving and inference infrastructure
• Contributions to open-source projects
• Experience at a high-growth startup (Series A through
  
  C)
• Infrastructure-as-code experience with Terraform or Pulumi