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Salary
$180k – $280k per year
Location
In office (New York)
Seniority
Senior · 5+ years exp

Confirmed on the employer's own hiring board on Oct 22, 2026. First seen by Alion on Dec 19, 2025. Reflexivity scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Designed for institutional investors, Reflexivity combines trusted data from S&P Global, LSEG Datastream, Cboe, Nasdaq, and more with explainable AI to surface insights - not noise.
Backed by Greycroft

You build backend systems that stay up when things get ugly.

You care about correctness, performance, and clarity over cleverness.

You want your code to power decisions involving real money.

If you have only worked on internal tools or low-impact services, this is not the role.

The Role, In Plain English

You will build the backend systems that power Reflexivity’s AI-driven investment platform.

This role exists because scale, data complexity, and latency matter deeply in finance.

You will work closely with AI and product teams to ship production-grade systems.

What You’ll Be Responsible For

  • Build and maintain Golang services that power core product workflows
  • Design APIs and data pipelines used by AI and reasoning systems
  • Improve system performance, reliability, and observability
  • Review and challenge designs to keep systems simple and scalable
  • Debug production issues with speed and discipline

What “Good” Looks Like in This Role

After 3 months:

You ship production code confidently and understand system trade-offs.

After 6 months:

You own critical services and improve their performance or reliability.

After 12 months:

You influence architecture decisions and mentor other engineers.

Who You Are (Must-Haves)

  • 5 plus years backend engineering experience
  • Strong Golang experience in production systems
  • Startup experience on a core product
  • Experience working with data-heavy systems
  • Comfortable using AI-assisted coding tools daily
  • Fintech or investment domain exposure

Nice-to-Haves

  • Experience supporting ML or LLM systems
  • Distributed systems or low-latency data pipelines

How We Work

  • Engineers own systems end to end
  • Clear accountability and direct feedback
  • In-office team with high trust and high ownership

Why This Role Is Worth Your Time

  • Work on systems that directly affect investor outcomes
  • Strong technical ownership
  • High bar engineering culture without bureaucracy

Compensation & Practicalities

  • $180,000 to $280,000 depending on experience
  • Equity included
  • In-office role based in New York
  • No agencies
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