SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
OpenAI is seeking a hands-on Engineering Manager to lead the ChatGPT Library team, which builds the persistence layer enabling people and organizations to collaborate with increasingly capable AI systems. The Library provides users with a durable place for files, context, and creations, forming a substrate between humans and agents—a foundation for AI that can remember, retrieve, and act on the right context over time.
The team sits within the Personalization organization and partners closely with product, design, research, model, and infrastructure teams. The work helps models become a useful second brain for individuals (e.g., answering "What did I work on last week?") and supports enterprise use cases that turn company knowledge into accessible, actionable context.
In this role, you will lead and coach a team of approximately 9–10 engineers while creating clarity, accountability, and a healthy execution rhythm. You will own the engineering roadmap for Library, working with product and design partners to prioritize the highest-impact problems. You'll set a high bar for product quality, technical excellence, reliability, privacy, and user trust, and provide hands-on technical leadership through architecture reviews, prototyping, debugging, and coding when it accelerates the team or unblocks critical paths.
You will build systems that allow AI products to persist, retrieve, and use personal and organizational context effectively. You'll partner across Personalization, model, research, infrastructure, enterprise, and third-party integration teams to deliver cohesive end-to-end experiences. You'll navigate ambiguity, make pragmatic tradeoffs, and turn emerging AI capabilities into a clear product and engineering plan. You'll also hire exceptional engineers and develop technical leaders who can scale the team's impact.
This is a technical leadership role for someone who can set a high product bar, build a strong team, shape architecture, and contribute directly when needed. The ideal candidate leads by example, is comfortable moving between people leadership, product decisions, technical design, and code, and brings founder or early-stage startup experience—the role requires urgency, sound judgment under ambiguity, and a willingness to operate across boundaries.
QUALIFICATIONS & REQUIREMENTS:
- Experience managing and developing high-performing engineering teams while remaining technically hands-on
- Strong software engineering foundation and comfort contributing production code in a modern codebase
- Track record of building and shipping user-facing products with a high quality bar, ideally in fast-moving or zero-to-one environments
- Founder, startup, or early-stage product experience; ability to create momentum with limited structure
- Ability to reason about distributed systems, data persistence, retrieval, permissions, collaboration, and the product implications of AI-native architectures
- Clear communication across engineering, product, design, research, and executive stakeholders
- Ability to balance long-term technical direction with near-term delivery; judgment on when to simplify, prototype, or invest for scale
- Deep commitment to building AI products that are useful, trustworthy, and intuitive for both individuals and organizations
