Senior Staff Software Engineer, Internal Tools
Listed on 2026-08-05
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Software Development
AI Engineer (Applied/Software), Backend Developer, Cloud Engineer - Software, Software Architect
Senior Staff Software Engineer, Internal Tools
Redwood City, CA (Hybrid)
The Chan Zuckerberg Initiative was founded in 2015 by Priscilla Chan and Mark Zuckerberg to harness the power of technology to pursue some of society's most ambitious goals — from curing or preventing all disease to transforming how students learn.
At CZI, you'll join a deeply collaborative, mission-driven community where your work helps drive breakthroughs across our flagship nonprofit organizations, Biohub and Learning Commons. Whether enabling scientific breakthroughs via open science and AI-powered biology or strengthening the tools teachers and students rely on every day, your contributions help turn bold ideas into real-world impact.
Our teams operate at the intersection of innovation and scale, building the infrastructure, partnerships, and capabilities that allow scientists, educators, and innovators to tackle some of the most complex challenges of our time — and to do so with urgency, integrity, and optimism.
The OpportunityOur Central Tech team provides technology and security support for CZI and our grantees. We believe that Engineering, IT and Security are most effective when in sync and learning from each other on a daily basis. Across our three pillars of Infrastructure, Security, and Grantee & Partner Support, we enable our teams to achieve their goals faster and more securely. We leverage technology to automate manual processes, constantly innovate to optimize operations, provide first-class support, and build solutions to enable the scale and execution of our business partners' strategies and initiatives.
This role is about building the internal tools and AI-powered workflows that make CZI's employees more effective at the work they do. As the Senior Staff Software Engineer for Internal Tools, you'll set technical direction for the platform — the applications, agents, integrations, and knowledge infrastructure that turn back-office work into something teams can do faster, better, and with more leverage.
You'll lead the hardest builds hands-on and be the senior technical voice for this work across the function.
This is a high-autonomy, high-impact tech lead IC role. The team is intentionally small — the leverage comes from depth and design discipline, not headcount. Over time, you may take on management of contingent engineering support and a small number of engineers as the team's scope develops. Success looks like applications business teams actually adopt, technical patterns that get reused instead of rebuilt every quarter, and an engineering bar that holds without needing to be enforced.
WhatYou'll Do
- Set technical strategy by defining the architecture and technical roadmap e across the stack — applications, AI agents and workflows, integrations, and knowledge infrastructure
- Architect and maintain reliable, scalable production applications with a focus on infrastructure automation and governance
- Design and build the AI layer — custom agents, workflows, and the knowledge and retrieval substrate that lets them reason over connected enterprise data
- Tech-lead a small team: set the design and code review bar, partner with engineers on what good looks like, mentor contingent engineering support
- Partner with senior business stakeholders across the org and with embedded engineers in Investments, Biohub, and Learning Commons
- 12+ years building production software systems, with meaningful time as a Senior Staff or Principal IC tech-leading small teams
- Strong full-stack engineering fundamentals — comfortable shipping production applications, backend services, and the integration layer between them
- Experience operating cloud infrastructure for production systems using industry-standard best practices like Infrastructure as Code (IaC)
- Strong API integration experience at the enterprise SaaS layer — auth, rate limits, schema drift, failure modes
- Working fluency with MCP, LLM tool/function calling, current agent frameworks, and retrieval/knowledge infrastructure (knowledge graphs, vector stores, RAG)
- Comfort with ambiguity; ability to make progress when requirements are evolving
- Strong stakeholder fluency; you can…
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