Applied AI Engineer, Investments

Chan Zuckerberg Initiative•Redwood City, CA

1d•$134,000 - $183,700•Hybrid

About The Position

The Chan Zuckerberg Initiative (CZI) 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 Investments team is a key partner in enabling Biohub’s pioneering work to combine frontier AI with frontier biology to solve disease and Learning Commons’ mission to build AI infrastructure that aligns how students learn with the tools that shape their learning experiences. The Investment team's goal is to build a world-class investment portfolio to help fund CZI’s ongoing operations over the long term. This includes providing the resources needed to support our work. Our program pursues a “manager of managers” approach, scouring the globe to find extraordinary investment organizations that invest across a wide spectrum of styles and asset classes. As an Applied AI Engineer on the Investments team, you will help build AI-powered applications and workflows that enhance investment research, decision-making, and operational efficiency. Working closely with investment and operations professionals, you will develop tools and data solutions that make information more accessible, automate manual processes, and generate actionable insights across the investment lifecycle. This is an opportunity for a new grad or early-career engineer who is excited about applying artificial intelligence, software engineering, and data technologies to real-world challenges. You will gain exposure to financial markets, institutional investing, and modern AI systems while helping shape how a sophisticated investment organization leverages emerging technologies to improve decision-making and scale its operations. The ideal applicant combines strong technical fundamentals with intellectual curiosity, analytical thinking, and a builder mindset. They enjoy learning new technologies, solving complex problems, and translating ideas into practical solutions. This role is ideal for someone who wants to grow as an engineer at the intersection of AI, data, and investing. You will have the opportunity to build impactful systems, learn from experienced investment professionals, and help define how AI is applied within a modern institutional investment office.

Requirements

Bachelor’s or Master’s degree in Computer Science, Software Engineering, Mathematics, Statistics, Engineering, Finance, Economics, or a related field, or equivalent practical experience.
Strong interest in financial markets, investing, and applying technology to improve investment decision-making.
Strong programming skills in Python or a similar language, with experience building software applications through internships, research, coursework, hackathons, or personal projects.
Solid foundation in computer science fundamentals, including algorithms, data structures, software design principles, APIs, databases, and data processing.
Interest in artificial intelligence, large language models, workflow automation, and emerging technologies.
Exposure to software engineering, machine learning, data science, quantitative research, or related technical disciplines.
Strong analytical, problem-solving, written communication, and collaboration skills, with the ability to work effectively with both technical and non-technical partners.

Nice To Haves

Familiarity with modern development tools, cloud technologies, data analysis, or investment-related concepts is a plus.

Responsibilities

Build AI-enabled applications and workflows that support investment research, manager monitoring, reporting, and operational processes.
Develop integrations with internal and external data sources to improve access to information and reduce manual work.
Contribute to data pipelines, automation workflows, and reporting systems that improve efficiency and data accessibility.
Organize, process, and prepare structured and unstructured data for use in AI applications and analytics tools.
Implement data validation, monitoring, and quality checks to improve the reliability of investment data.
Partner with investment and operations team members to understand business needs and help develop technical solutions.
Explore and prototype emerging AI technologies, including large language models, retrieval systems, and workflow automation tools.
Participate in code reviews, testing, documentation, and software engineering best practices.
Troubleshoot technical issues and contribute to system improvements.
Stay current on developments in artificial intelligence, software engineering, data systems, and financial technology.