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Clera

Full Stack Engineer

remote (Remote)$170k–$220kfulltimemidAdded yesterday

About this role

Join a Series A fintech startup's four-person engineering team to build and operate an AI-powered investing platform at scale. You'll take ownership of iOS, Node.js backend services, and AWS infrastructure, reporting directly to the Head of Engineering and handling production debugging, system optimization, and platform reliability across the full stack.

What you'll do

  • Investigate and resolve complex production issues spanning iOS, backend, database, and AWS infrastructure
  • Build and maintain Node.js/TypeScript backend services with focus on reliability, correctness, and performance
  • Optimize MongoDB queries, indexes, and data access patterns for scale
  • Strengthen AWS infrastructure stability and improve observability via structured logging and CloudWatch
  • Reduce recurring bug classes through better validation, error handling, and system boundaries
  • Improve CI/CD pipelines and release processes to minimize production risk

What they're looking for

  • Node.js and TypeScript
  • MongoDB performance tuning and data modeling
  • AWS (Elastic Beanstalk, EC2, deployments, monitoring)
  • Production debugging across full stack
  • iOS development (Swift/SwiftUI preferred)
  • System observability and structured logging
  • CI/CD and release engineering
  • Fintech or payments domain knowledge

Benefits

  • Equity participation in well-funded Series A startup
  • Visa sponsorship available
  • High-ownership role at critical growth inflection point
  • Direct reporting to Head of Engineering
  • Collaborative four-person engineering team environment
  • Opportunity to shape platform architecture at scale
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Clera

Clera builds an agentic operating system that automates complex workflows and processes through AI agents, with a platform designed to simplify distributed infrastructure management for developers. The company is hiring Founding Engineers, Customer Engineers, and Product Engineers to develop both backend systems and user-facing interfaces across their AI automation products.

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Likely interview questions

  • Walk us through a complex production incident you've debugged across multiple system layers—how did you approach root cause analysis?
  • Describe your experience optimizing MongoDB performance in a high-scale environment. What indexing or query patterns have you improved?
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