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Ajax

Full Stack Engineer

New York City$180k–$220kfulltimemidAdded 1 month ago

About this role

Ajax is a B2B SaaS startup solving time-tracking pain for law firms with an AI-powered tool that automatically generates accurate billing entries. We're seeking a Full Stack Engineer to join our customer-obsessed team in NYC and help scale our product for legal professionals.

What you'll do

  • Build and optimize full-stack features for our time-tracking application serving law firms
  • Collaborate directly with customers and GTM team to understand product needs and validate solutions
  • Develop across our tech stack including React frontend, Flutter mobile app, and Python backend
  • Participate in rapid iteration cycles to drive pilot conversions and customer activation
  • Contribute to backlog planning with input from both engineering and go-to-market perspectives
  • Support continuous optimization of system performance and user experience

What they're looking for

  • Full-stack web development (React, Python)
  • Mobile app development (Flutter)
  • Backend optimization and async programming
  • Data analysis and hypothesis-driven development
  • Customer-centric problem solving
  • Real-time systems and low-latency optimization
  • API design and integration
  • Collaborative software architecture

Benefits

  • $180-230k base salary plus meaningful equity
  • Full health, dental, and vision coverage
  • In-person collaboration in NYC with close-knit engineering and GTM teams
  • Direct customer interaction and feedback loops
  • Rapid hiring process (under 1 week, under 4 hours total)
  • Team meals and social events celebrating wins together
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Ajax

Ajax builds AI-powered automation tools that eliminate time tracking and billing pain for professional services firms like law firms, accounting, and consulting practices. The company is hiring Full Stack Engineers and Design Engineers to scale the product and shape its core features.

View all jobs at Ajax

Likely interview questions

  • Ajax sits on customers' computers and generates time entries—walk us through how you'd approach building a reliable system that captures user activity without being intrusive or causing performance issues.
  • Tell us about a time you optimized backend code for latency (like the p99 entry latency work mentioned here). What tools did you use to identify bottlenecks?
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