Sr Staff Software Engineer - Backend (python)

PayPal PayPal · Fintech · San Jose, CA +2 · Software Engineering

Senior Staff Backend Engineer at PayPal focusing on architecting, building, and operating scalable distributed systems. The role involves defining backend architecture strategy, leading large-scale initiatives, and mentoring engineers. A key aspect is applying machine learning or LLM techniques for personalization, risk, search, and driving adoption of AI-assisted development and LLM-powered product features.

What you'd actually do

  1. Makes technical decisions affecting multiple teams, crossing organizational boundaries
  2. Establishes conventions & processes to be followed by other employees
  3. Actions determine the utilization of company resources (people, money, assets) and affect the effectiveness of the company
  4. Handles multiple, multi-team initiatives simultaneously, using judgement to prioritize among more issues than can be handled individually.
  5. Understands evolving industry capabilities & practices and can judiciously apply up--to-date information for optimal results

Skills

Required

  • 8+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.
  • 8+ years architecting, building, and operating cloud‑native, distributed systems at meaningful scale.
  • Deep understanding of service design, data modeling, asynchronous messaging, and API craftsmanship, with a privacy‑by‑design approach.

Nice to have

  • Track record of raising the engineering bar through design standards, automated quality gates, SLO ownership, and a culture of blameless post‑mortems.
  • You prototype rapidly, run A/B tests, and turn promising spikes into reliable production services.
  • Hands‑on experience applying machine‑learning or large‑language‑model techniques for personalization, risk, search, or developer productivity; ready to lead our adoption of AI‑assisted development and LLM‑powered product features.
  • Explain complex trade‑offs in plain language and help seasoned engineers grow through candid feedback and sponsorship.
  • Able to align product, design, and compliance partners around a technical vision and rally other teams to deliver on it.

What the JD emphasized

  • 8+ years architecting, building, and operating cloud‑native, distributed systems at meaningful scale.
  • Track record of raising the engineering bar through design standards, automated quality gates, SLO ownership, and a culture of blameless post‑mortems.
  • Hands‑on experience applying machine‑learning or large‑language‑model techniques for personalization, risk, search, or developer productivity; ready to lead our adoption of AI‑assisted development and LLM‑powered product features.

Other signals

  • AI-assisted development
  • LLM-powered product features
  • personalization
  • risk
  • search