Sr IT Software Engineer

Palo Alto NetworksSanta Clara, CA
1d$106,000 - $170,500Onsite

About The Position

Your Career The IT Engineering team builds AI-first enterprise systems that power critical business workflows across the company. This role will focus on advancing finance-related initiatives, partnering closely with Finance stakeholders to modernize and automate high-impact processes. We operate at the intersection of full-stack application development, cloud-native automation, and applied AI. The role requires strong software engineering fundamentals combined with the ability to design scalable systems, integrate AI responsibly, and deliver measurable business impact. You will work across modern web development (TypeScript, NestJS, React), cloud-native services on GCP, and AI-driven architectures (Vertex AI, RAG pipelines, agent orchestration). We expect engineers to uphold high technical standards, think in systems, and continuously apply AI to improve both product outcomes and engineering velocity.

Requirements

  • Bachelor’s or Master’s in Computer Science, Engineering, or related field (or equivalent experience)
  • 3+ years of software engineering experience
  • Strong full-stack development experience (React, Node.js/NestJS, TypeScript, SQL)
  • Experience deploying cloud-native applications (GCP preferred)
  • Practical experience integrating AI services (Vertex AI, OpenAI, RAG, embeddings, tool/function calling)
  • Experience with CI/CD, containerization, and production observability
  • Strong debugging, system thinking, and attention to detail
  • Demonstrated ability to independently deliver complex projects

Nice To Haves

  • Dual major in Finance or demonstrated domain exposure in Finance is a plus

Responsibilities

  • Design and develop full-stack enterprise applications supporting finance initiatives using TypeScript, NestJS, React, and SQL
  • Own major features or services from design through production deployment
  • Build AI-integrated workflows (RAG pipelines, structured LLM calls, automation orchestration) with strong guardrails and evaluation practices
  • Integrate securely with finance systems and data sources to enable reliable automation
  • Establish high-quality testing, logging, tracing, and observability practices
  • Improve development velocity by leveraging AI coding tools responsibly and validating outputs
  • Contribute architectural input in design reviews and challenge weak designs
  • Debug complex production issues and implement safeguards to prevent recurrence
  • Mentor junior engineers through code reviews and pairing
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